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SUGIURA Yousuke
| Mathematics, Electronics and Informatics Division | Assistant Professor |
| Department of Information and Computer Sciences |
Researcher information
■ Research Keyword■ Field Of Study
■ Career
- Apr. 2015 - Present, Saitama University, Graduate School of Science and Engineering, Assistant Professor
- Sep. 2023 - Mar. 2025, Saitama Medical University, Faculty of Medicine, Japan
- Apr. 2013 - Mar. 2015, Tokyo University of Science, Faculty of Industrial Science and Technology, Assistant Professor
- Apr. 2011 - Mar. 2013, Osaka University, Graduate School of Engineering Science, Doctor Course
- Apr. 2009 - Mar. 2011, Osaka University, Graduate School of Engineering Science, Master Course
Performance information
■ Paper- ML: Generalized Additive Model for Spectrum Sensing in Nakagami-m Fading Channel With Complex Generalized Gaussian Distribution Noise
M. T. Ahmed; M. Haque; Y. Sugiura; T. Shimamura
IEEE Access, Volume：13, First page：84488, Last page：84498, May 2025, [Reviewed]
English, Scientific journal - Frequency-Domain Weighted FxLMS Algorithm for Feedback Active Noise Control
Yosuke SUGIURA; Ryota NOGUCHI; Tetsuya SHIMAMURA
IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences, Volume：E108.A, Number：3, First page：323, Last page：331, Mar. 2025, [Reviewed], [Lead]
Institute of Electronics, Information and Communications Engineers (IEICE), English, Scientific journal
DOI：https://doi.org/10.1587/transfun.2024smp0008
DOI ID：10.1587/transfun.2024smp0008, ISSN：0916-8508, eISSN：1745-1337 - Acoustic Feature Extraction Method for Piglet Call Detection
Tenma Nakano; Yosuke Sugiura; Tetsuya Shimamura; Yoshiyuki Nakamura; Ayaka Miyazaki
Lecture Notes in Electrical Engineering, First page：332, Last page：341, Feb. 2025, [Reviewed]
Springer Nature Singapore, In book
DOI：https://doi.org/10.1007/978-981-96-1535-3_33
DOI ID：10.1007/978-981-96-1535-3_33, ISSN：1876-1100, eISSN：1876-1119 - FxlogLMS+: Modified FxlogLMS Algorithm for Active Impulsive Noise Control
Aoi Haneda; Yosuke Sugiura; Tetsuya Shimamura
Lecture Notes in Electrical Engineering, First page：342, Last page：351, Feb. 2025, [Reviewed]
Springer Nature Singapore, In book
DOI：https://doi.org/10.1007/978-981-96-1535-3_34
DOI ID：10.1007/978-981-96-1535-3_34, ISSN：1876-1100, eISSN：1876-1119 - Real-Time Video Denoising Acceleration Using Pixel Shuffle and FP16
Riku Masuko; Yosuke Sugiura; Tetsuya Shimamura
Lecture Notes in Electrical Engineering, First page：322, Last page：331, Feb. 2025, [Reviewed]
Springer Nature Singapore, In book
DOI：https://doi.org/10.1007/978-981-96-1535-3_32
DOI ID：10.1007/978-981-96-1535-3_32, ISSN：1876-1100, eISSN：1876-1119 - Arrival Time Difference Estimation Based on GCC-PHAT for Multiple Loudspeakers
Riku Kasakura; Yosuke Sugiura; Tetsuya Shimamura
Lecture Notes in Electrical Engineering, First page：312, Last page：321, Feb. 2025, [Reviewed]
Springer Nature Singapore, In book
DOI：https://doi.org/10.1007/978-981-96-1535-3_31
DOI ID：10.1007/978-981-96-1535-3_31, ISSN：1876-1100, eISSN：1876-1119 - StereoLCM: Accelerating Stereo Image Generation Using Latent Consistency Model
Yukito Onuma; Yosuke Sugiura; Tetsuya Shimamura
Proceedings of 2025 RISP International Workshop on Nonlinear Circuits, Communications and Signal Processing, First page：1, Last page：4, Feb. 2025, [Reviewed]
International conference proceedings - A Variable Step-size for Weighted Frequency-domain Feedback Active Noise Control
Ryota Noguchi; Yosuke Sugiura; Tetsuya Shimamura
Proceedings of 2025 RISP International Workshop on Nonlinear Circuits, Communications and Signal Processing, First page：1, Last page：4, Feb. 2025, [Reviewed]
International conference proceedings - Investigation of Lightweight Techniques for Multi-task Automatic Modulation Classification
Naoyuki Funabashi; Yosuke Sugiura; Tetsuya Shimamura
Proceedings of 2025 RISP International Workshop on Nonlinear Circuits, Communications and Signal Processing, First page：1, Last page：4, Feb. 2025, [Reviewed]
International conference proceedings - Exploring the EmoBone Dataset with Bi-Directional LSTM for Emotion Recognition via Bone Conducted Speech
Md. Sarwar Hosain; Md. Rifat Hossen; Md. Uzzal Mia; Yosuke Sugiura; Tetsuya Shimamura
Proceedings of 2025 RISP International Workshop on Nonlinear Circuits, Communications and Signal Processing, Feb. 2025, [Reviewed]
International conference proceedings - Machine Learning Approach to Energy Detection Based Spectrum Sensing for Cognitive Radio Networks
Md. Tofail Ahmed; Mousumi Haque; Yosuke Sugiura; Tetsuya Shimamura
IEEJ Transactions on Electrical and Electronic Engineering, Jan. 2025, [Reviewed]
Abstract
Cognitive radio is an intelligent technology for wireless communication that optimizes the use of available frequency bands. Machine learning techniques can play an important role in spectrum sensing for cognitive radio networks to meet the rising traffic demand of wireless communication systems. The reliability of spectrum sensing methods depends on the prior knowledge of the noise to set a threshold. On the other hand, the success of a machine learning model relies on both the datasets and the accuracy of its learning algorithms. In this paper, we propose a spectrum sensing method for cognitive radio based on a machine learning algorithm in the conventional energy detection technique that removes the requirement to calculate the threshold. Initially, we introduce a method to build the dataset using the general concept of spectrum sensing based on the energy detection technique. The Naive Bayes supervised machine learning classification algorithm is implemented on the generated dataset for training, validation, and testing to sense the available spectrum. The proposed method is evaluated and tested using performance metrics such as confusion matrix, accuracy, precision, recall, F1 score, probability of detection, and probability of false alarm. In the simulation, the quadrature phase‐shift keying (QPSK) modulation scheme over the additive white Gaussian noise (AWGN) channel is considered. The experimental outcomes of the proposed method provide satisfactory and acceptable performance for spectrum sensing in cognitive radio networks. © 2025 Institute of Electrical Engineers of Japan and Wiley Periodicals LLC.
Wiley, Scientific journal
DOI：https://doi.org/10.1002/tee.24261
DOI ID：10.1002/tee.24261, ISSN：1931-4973, eISSN：1931-4981 - A Subjective Evaluation Dataset for GuitarSet
Takumi Hojo; Yosuke Sugiura; Nozomiko Yasui; Tetsuya Shimamura
2024 International Symposium on Intelligent Signal Processing and Communication Systems (ISPACS), First page：1, Last page：5, Dec. 2024, [Reviewed]
IEEE, International conference proceedings
DOI：https://doi.org/10.1109/ispacs62486.2024.10868890
DOI ID：10.1109/ispacs62486.2024.10868890 - Lightweight Frequency Domain Hybrid Active Noise Control System for Uncorrelated Disturbance
Shosuke Namekawa; Yosuke Sugiura; Tetsuya Shimamura
2024 International Symposium on Intelligent Signal Processing and Communication Systems (ISPACS), First page：1, Last page：5, Dec. 2024, [Reviewed]
IEEE, International conference proceedings
DOI：https://doi.org/10.1109/ispacs62486.2024.10868228
DOI ID：10.1109/ispacs62486.2024.10868228 - Detection of Practical Primary Users in Severe Noise Environments for Cognitive Radio
Mousumi Haque; Yosuke Sugiura; Tetsuya Shimamura
American Journal of Networks and Communications, Volume：13, Number：2, First page：97, Last page：107, Oct. 2024, [Reviewed]Cognitive radio (CR) is one of the compelling ideas to solve the spectrum scarcity problem for rapid developments in wireless communication systems. In CR systems, signal detection for orthogonal frequency division multiplexing (OFDM) systems in severe noise environments is a key challenge. The area of practical primary user detection has not been explored in depth. The proposed method is an effective method for sensing OFDM applications, which are the practical primary users, for low signal-to-noise (SNR) cases. In the proposed method, the parallel combination of the comb filter and the time-domain autocorrelation function is exploited. The detection performance is measured for various OFDM system applications, including the IEEE 802.11a wireless LAN (WLAN) radio interface, long-term evaluation (LTE), and digital audio broadcasting (DAB) for various CP ratios under 16-quadrature amplitude modulation (16-QAM) and 64-quadrature amplitude modulation (64-QAM) over multipath Rayleigh fading channels with additive white Gaussian noise (AWGN). Furthermore, the OFDM sensing is possible in the presence of noise uncertainty and the sensing performance is compared under consideration with and without noise uncertainty cases. The simulation results demonstrated that our proposed method undoubtedly improves the sensing performances (up to 11 dB SNR gain) of practical primary users more than the conventional spectrum detection methods for low SNR cases.
Science Publishing Group, Scientific journal
DOI：https://doi.org/10.11648/j.ajnc.20241302.12
DOI ID：10.11648/j.ajnc.20241302.12, ISSN：2326-893X, eISSN：2326-8964 - Lightweight Underwater Image Enhancement via Impulse Response of Low-Pass Filter Based Attention Network
May Thet Tun; Yosuke Sugiura; Tetsuya Shimamura
2024 IEEE International Conference on Image Processing (ICIP), First page：1697, Last page：1703, Oct. 2024, [Reviewed]
IEEE, International conference proceedings
DOI：https://doi.org/10.1109/icip51287.2024.10647440
DOI ID：10.1109/icip51287.2024.10647440 - Frequency-domain Feedback Active Noise Control using Weighted LMS Algorithm
Ryota Noguchi; Yosuke Sugiura; Tetsuya Shimamura
2024 32nd European Signal Processing Conference (EUSIPCO), First page：211, Last page：215, Aug. 2024, [Reviewed]
IEEE, International conference proceedings
DOI：https://doi.org/10.23919/eusipco63174.2024.10715075
DOI ID：10.23919/eusipco63174.2024.10715075 - A Novel Tight Closed-Form Capacity Analysis for Rician Fading Wireless Channel Using Small Limit Argument Approximation
Md. Sohidul Islam; Yosuke Sugiura; Tetsuya Shimamura
Journal of Signal Processing, Volume：28, Number：4, First page：119, Last page：122, Jul. 2024, [Reviewed]
Research Institute of Signal Processing, Japan, Scientific journal
DOI：https://doi.org/10.2299/jsp.28.119
DOI ID：10.2299/jsp.28.119, ISSN：1342-6230, eISSN：1880-1013 - EmoBone: A Multinational Audio Dataset of Emotional Bone Conducted Speech
Md. Sarwar Hosain; Yosuke Sugiura; M. Shahidur Rahman; Tetsuya Shimamura
IEEJ Transactions on Electrical and Electronic Engineering, Volume：19, Number：9, First page：1492, Last page：1506, May 2024, [Reviewed]
Abstract
This paper introduces EmoBone, a comprehensive audio‐only emotional bone‐conducted speech dataset featuring speakers from various countries. The dataset comprises speeches from 28 individuals representing 10 different nations, with each participant delivering 10 sentences designed to evoke distinct emotions. In addition to an air‐conducted microphone, the recordings utilized bone conduction technology, transmitting sound directly to the speakers' inner ears, ensuring high‐quality emotional speech recordings. To assess the validity of the dataset, 80 university students from Bangladesh listened to the recordings and successfully identified the expressed emotions with an accuracy exceeding 76%. Statistical methods were also employed to evaluate the reliability of the dataset, revealing a high level of agreement among raters. EmoBone, with a cumulative duration surpassing 19 h and 15 680 unique utterances, stands as the most extensive emotional speech dataset available. This makes it a valuable tool for studying how emotional speech varies across cultures. Furthermore, due to its utilization of bone conduction technology, EmoBone facilitates the study of acoustic features in emotional speech from diverse dimensions. The data that supports the findings of this study is available upon reasonable request. © 2024 Institute of Electrical Engineers of Japan and Wiley Periodicals LLC.
Wiley, Scientific journal
DOI：https://doi.org/10.1002/tee.24110
DOI ID：10.1002/tee.24110, ISSN：1931-4973, eISSN：1931-4981 - Regularized Modified Covariance Method for Spectral Analysis of Bone-Conducted Speech
Ohidujjaman; Yosuke Sugiura; Nozomiko Yasui; Tetsuya Shimamura; Hisanori Makinae
Journal of Signal Processing, Volume：28, Number：3, First page：77, Last page：87, May 2024, [Reviewed]
Research Institute of Signal Processing, Japan, Scientific journal
DOI：https://doi.org/10.2299/jsp.28.77
DOI ID：10.2299/jsp.28.77, ISSN：1342-6230, eISSN：1880-1013 - Packet Loss Concealment Estimating Residual Errors of Forward-Backward Linear Prediction for Bone-Conducted Speech
Ohidujjaman; Nozomiko Yasui; Yosuke Sugiura; Tetsuya Shimamura; Hisanori Makinae
International Journal of Advanced Computer Science and Applications, Volume：15, Number：4, First page：1263, Last page：1268, Apr. 2024, [Reviewed]
The Science and Information Organization, Scientific journal
DOI：https://doi.org/10.14569/ijacsa.2024.01504126
DOI ID：10.14569/ijacsa.2024.01504126, ISSN：2158-107X, eISSN：2156-5570 - Packet Loss Concealment Using Regularized Modified Linear Prediction through Bone-Conducted Speech
Ohidujjaman; Yosuke Sugiura; Tetsuya Shimamura; Hisanori Makinae
First page：142, Last page：146, Mar. 2024, [Reviewed]
DOI：https://doi.org/10.1145/3655755.3655774
DOI ID：10.1145/3655755.3655774 - Poisson–Gaussian Noise Removal for Low-Dose CT Images by Integrating Noisy Image Patch and Impulse Response of Low-Pass Filter in CNN
Tun May Thet; Sugiura Yosuke; Shimamura Tetsuya
Journal of Signal Processing, Volume：28, Number：2, First page：57, Last page：67, Mar. 2024, [Reviewed]
In this paper, we propose the incorporation of noisy image patches and the impulse response of a low-pass filter (LPF) in a convolutional neural network (CNN) to denoise Poisson–Gaussian noise in low-dose computed tomography (LDCT) images. The approach is referred to as fast and flexible denoising CNN (FFDNet)-impulse response (FFDNet-IR) in this paper. The power spectrum sparsity LPF (SLPF) allows low-frequency components to pass through while suppressing higher frequency components by the sparsity approach of the power spectrum, and it is employed to determine the impulse response of LPF. Three well-known types of LPF, namely, Direct LPF, Gaussian LPF, and Butterworth LPF, are also considered to obtain the impulse response of LPF. In the FFDNet-IR, both the noisy image patches and the IR of the LPF are sequentially inputted into the FFDNet to eliminate the Poisson–Gaussian noise. This approach enhances the denoising performance in LDCT images compared with the conventional FFDNet in the evaluation metrics of the peak signal-to-noise ratio (PSNR), structural similarity (SSIM), and feature similarity (FSIM). Moreover, the FFDNet-IR trained with the Poisson–Gaussian noise model demonstrates the generalization ability and effectively eliminates only Poisson or Gaussian noise. The experiments indicate that the FFDNet-IR more effectively suppresses the noise artifacts and preserves image details compared with the baseline FFDNet, as well as traditional methods such as block-matching and 3D filtering (BM3D) and nonlocal mean (NLM) for LDCT image denoising.
Research Institute of Signal Processing, Japan, English, Scientific journal
DOI：https://doi.org/10.2299/jsp.28.57
DOI ID：10.2299/jsp.28.57, ISSN：1342-6230, eISSN：1880-1013 - Blind Image Quality Assessment Using Naturalness Aware Multiscale Features
Lynn Nay Chi; Sugiura Yosuke; Shimamura Tetsuya
Journal of Signal Processing, Volume：28, Number：2, First page：45, Last page：55, Mar. 2024, [Reviewed]
We propose a blind image quality assessment (BIQA) method of using the multitask-learning-based end-to-end convolutional neural network (CNN) approach. The architecture of the proposed method is integrated by two streams. In the first stream, multiscale image features are extracted by using the inception and pyramid pooling modules. Natural scene statistics (NSS)-based features are extracted in the second stream. The two streams are then integrated into fully connected layers to estimate the image quality score. The performance of the proposed method is validated with four public IQA databases and the obtained experimental results show the superiority of the proposed method over conventional IQA methods.
Research Institute of Signal Processing, Japan, English, Scientific journal
DOI：https://doi.org/10.2299/jsp.28.45
DOI ID：10.2299/jsp.28.45, ISSN：1342-6230, eISSN：1880-1013 - Joint Training of Noisy Image Patch and Impulse Response of Low-Pass Filter in CNN for Image Denoising
Thet Tun May; Sugiura Yosuke; Shimamura Tetsuya
Journal of Signal Processing, Volume：28, Number：1, First page：1, Last page：17, Jan. 2024, [Reviewed]
In this paper, we propose the sequential input of a noisy image patch and the impulse response of a low-pass filter (LPF) in the training of the conventional fast and flexible solution for CNN-based image denoising (FFDNet) architecture, which enhances denoising performance and edge preservation and achieves high perceptual quality. The proposed method consists of two steps. In the first step, the power spectrum sparsity is utilized to determine the impulse response of LPF and the resulting impulse response is added to the noisy image patch in a sequential form to estimate the low- and high-frequency components of the input image. In this step, the use of three different types of LPF is also considered. In the second step, the FFDNet architecture, a deep-learning-based image denoiser, is employed. The proposed method achieves satisfactory denoising performance for grayscale and color datasets on synthetic additive white Gaussian noise (AWGN) in terms of the peak signal-to-noise ratio (PSNR), structural similarity index (SSIM), feature similarity index (FSIM), and learned perceptual image patch similarity (LPIPS) compared with the original FFDNet. The performances on realistic noise and for chest X-ray images are also investigated.
Research Institute of Signal Processing, Japan, English, Scientific journal
DOI：https://doi.org/10.2299/jsp.28.1
DOI：https://doi.org/10.2299/jsp.28.57_references_DOI_TBPYhwBzSB59IXoibpFrP1Wsd3f
DOI ID：10.2299/jsp.28.1, ISSN：1342-6230, eISSN：1880-1013 - Blind Noisy Image Quality Assessment Using Spatial, Frequency and Wavelet Statistical Features
Chi Lynn Nay; Sugiura Yosuke; Shimamura Tetsuya
Journal of Signal Processing, Volume：28, Number：1, First page：19, Last page：27, Jan. 2024, [Reviewed]
In this paper, we propose a blind noisy image quality estimation method of simultaneously utilizing three statistical features extracted from three different domains of the input noisy image. The statistical features used in this paper are (i) eigen-based variance by the covariance matrix of image blocks in the spatial domain, (ii) the spectral entropy of the power spectrum in the frequency domain, and the standard deviation in the wavelet domain. The extracted statistical features are fed into an extreme learning machine algorithm for mapping into perceptual quality scores. The model is trained and tested on images with six common noise distortion types commonly occurring in real-world applications: additive white Gaussian noise, additive Gaussian noise in color component, high-frequency noise, masked noise, impulse noise, and multiplicative noise. For the CSIQ, TID2008, TID2013, and KADID10k databases, the experimental results show that our method covers noise distortions wider than those of the conventional methods and achieves consistently better performance for blind noisy image quality assessment.
Research Institute of Signal Processing, Japan, English, Scientific journal
DOI：https://doi.org/10.2299/jsp.28.19
DOI ID：10.2299/jsp.28.19, ISSN：1342-6230, eISSN：1880-1013 - Deep-Learning-Based Speech Emotion Recognition Using Synthetic Bone-Conducted Speech
Hosain Md. Sarwar; Sugiura Yosuke; Yasui Nozomiko; Shimamura Tetsuya
Journal of Signal Processing, Volume：27, Number：6, First page：151, Last page：163, Nov. 2023, [Reviewed]
Speech emotion recognition has drawn extensive attention in recent years. We propose deep learning (DL)-based speech emotion recognition using synthetic bone-conducted (BC) speech. In our proposed model, air-conducted(AC) speech is transformed to BC speech using an infinite impulse response (IIR) filter. Data augmentation techniques are utilized and the parameters of convolutional neural network (CNN) models are modified to enhance the accuracy of the proposed model. Simulation results demonstrate that the proposed model outperforms the existing models in terms of recognition accuracy for BC speech. The accuracy of the proposed model is 72.50% for BC speech, whereas that of the existing model is 69.83% for AC speech. This is because BC speech can enhance low-frequency components, which is important for recognizing emotions.
Research Institute of Signal Processing, Japan, English, Scientific journal
DOI：https://doi.org/10.2299/jsp.27.151
DOI ID：10.2299/jsp.27.151, ISSN：1342-6230, eISSN：1880-1013 - Image Denoising by Incorporating Noisy Image Patch and Impulse Response of Low-Pass Filter in CNN Learning
May Thet Tun; Yosuke Sugiura; Tetsuya Shimamura
First page：721, Last page：722, Oct. 2023, [Reviewed]
English, International conference proceedings
DOI：https://doi.org/10.1109/gcce59613.2023.10315451
DOI：https://doi.org/10.2299/jsp.28.57_references_DOI_KarGpK2lTjlbqin5IyHbHLAPiZj
DOI ID：10.1109/gcce59613.2023.10315451 - Noise Specific Blind Image Quality Assessment Using Three Statistical Features
Nay Chi Lynn; Yosuke Sugiura; Tetsuya Shimamura
First page：164, Last page：165, Oct. 2023, [Reviewed]
English, International conference proceedings
DOI：https://doi.org/10.1109/gcce59613.2023.10315629
DOI ID：10.1109/gcce59613.2023.10315629 - Packet Loss Compensation for VoIP through Bone‐Conducted Speech Using Modified Linear Prediction
Ohidujjaman; Nozomiko Yasui; Yosuke Sugiura; Tetsuya Shimamura; Hisanori Makinae
Volume：18, Number：11, First page：1781, Last page：1790, Aug. 2023, [Reviewed]
English, Scientific journal
DOI：https://doi.org/10.1002/tee.23907
DOI：https://doi.org/10.2299/jsp.28.77_references_DOI_ZLg9atd3CNBos0qGhAgMRnRywcZ
DOI ID：10.1002/tee.23907, ISSN：1931-4973, eISSN：1931-4981 - Distributed Blind Equalization with Block-Adaptive Approach on Wireless Sensor Network.
Sulin Chi; Yosuke Sugiura; Tetsuya Shimamura
2023 IEEE SENSORS(SENSORS), First page：1, Last page：4, 2023, [Reviewed]
IEEE, International conference proceedings
DOI：https://doi.org/10.1109/SENSORS56945.2023.10325095
DOI ID：10.1109/SENSORS56945.2023.10325095, DBLP ID：conf/ieeesensors/ChiSS23 - Two-Stage Filter Response Normalization Network for Real Image Denoising
Yuwen Tai; Sugiura Yosuke; Yasui Nozomiko; Shimamura Tetsuya
Journal of Signal Processing, Volume：26, Number：6, First page：183, Last page：187, Nov. 2022, [Reviewed]
In this paper, we propose a two-stage network for real image denoising with filter response normalization, named as two-stage filter response normalization network (TFRNet). In TFRNet, we propose a filter response normalization(FRN) block to extract features and accelerate the training of the network. TFRNet consists of two stages, at each stage of which we use the encoder-decoder structure based on U-Net. We also use the coordinate attention block(CAB), double channel downsampling module, double skip connection module, and convolutional (Conv) block in our TFRNet. With the help of these modules, TFRNet provides excellent results on both SIDD and DND datasets for real image denoising.
Research Institute of Signal Processing, Japan, English, Scientific journal
DOI：https://doi.org/10.2299/jsp.26.183
DOI ID：10.2299/jsp.26.183, ISSN：1342-6230, eISSN：1880-1013 - Air‐Conducted and Bone‐Conducted Speeches Combination for Noise‐Robust Pitch Extraction
Shiming Zhang; Yosuke Sugiura; Nozomiko Yasui; Tetsuya Shimamura
Volume：17, First page：1061, Last page：1071, Mar. 2022, [Reviewed]
English, Scientific journal
DOI：https://doi.org/10.1002/tee.23596
DOI ID：10.1002/tee.23596, ISSN：1931-4973, eISSN：1931-4981 - Bone‐Conducted Speech Synthesis Based on Least Squares Method
Shiming Zhang; Yosuke Sugiura; Tetsuya Shimamura
Volume：17, Number：3, First page：425, Last page：435, Jan. 2022, [Reviewed]
English, Scientific journal
DOI：https://doi.org/10.1002/tee.23531
DOI：https://doi.org/10.2299/jsp.27.151_references_DOI_BxVwCaPUkwHkUOoyr6mmTFkySWM
DOI ID：10.1002/tee.23531, ISSN：1931-4973, eISSN：1931-4981 - Speech Enhancement Network with Unsupervised Attention using Invariant Information Clustering
Y. Sugiura; S. Nagamori; T. Shimamura
Proceedings of 2021 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC), First page：406, Last page：409, Dec. 2021, [Reviewed], [Lead]
English, International conference proceedings - Adversarial Training Using Inter/Intra-Attention Architecture for Speech Enhancement Network
Y. SUGIURA; T. SHIMAMURA
Proceedings of 2020 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC), First page：242, Last page：246, Dec. 2020, [Reviewed], [Lead]
English, International conference proceedings - Pitch Extraction Using Fourth-Root Spectrum in Noisy Speech
Rahman Md. Saifur; Sugiura Yosuke; Shimamura Tetsuya
Journal of Signal Processing, Volume：24, Number：5, First page：207, Last page：222, Sep. 2020, [Reviewed]
In this paper, we present the use of the fourth-root spectrum instead of the log spectrum for pitch extraction in noisy environments. To obtain clear harmonics, lifter and clipping operations are performed. When the resulting spectrum is transformed into the time domain by the discrete Fourier transform, pitch detection is robust against narrow-band noise. When the same spectrum is amplified by power calculation and transformed into the time domain, pitch detection is robust against wide-band noise. These properties are investigated through exhaustive experiments in various noises. The required computational time is also studied.
Research Institute of Signal Processing, Japan, English, Scientific journal
DOI：https://doi.org/10.2299/jsp.24.207
DOI ID：10.2299/jsp.24.207, ISSN：1342-6230, eISSN：1880-1013, CiNii Articles ID：130007898997 - Utilization of windowing effect and accumulated autocorrelation function and power spectrum for pitch detection in noisy environments
Tetsuya Shimamura; Md. Saifur Rahman; Yosuke Sugiura
Volume：15, First page：1681, Last page：1690, Sep. 2020, [Reviewed]
English, Scientific journal
DOI：https://doi.org/10.1002/tee.23238
DOI ID：10.1002/tee.23238, ISSN：1931-4973, eISSN：1931-4981 - Speech Enhancement Based on Deep Neural Networks Considering Features of Speech Distribution
Tominaga Naoki; Sugiura Yosuke; Shimamura Tetsuya
Journal of Signal Processing, Volume：24, Number：4, First page：179, Last page：182, Jul. 2020, [Reviewed]
In this paper, we propose a new training architecture for speech enhancement based on deep neural networks. In the proposed architecture, the generative model producing the noiseless speech is trained so as to minimize the difference between two statistical distribution parameters of the clean speech and generated speech. From the experimental results, we verify that the proposed method can provide better results than the conventional method.
Research Institute of Signal Processing, Japan, English, Scientific journal
DOI：https://doi.org/10.2299/jsp.24.179
DOI ID：10.2299/jsp.24.179, ISSN：1342-6230, eISSN：1880-1013, CiNii Articles ID：130007873172 - Quantifying Noise Robustness of Bone-Conducted Speech.
Shiming Zhang; Yosuke Sugiura; Nozomiko Yasui; Tetsuya Shimamura
63rd IEEE International Midwest Symposium on Circuits and Systems(MWSCAS), First page：582, Last page：585, 2020, [Reviewed]
IEEE, English, International conference proceedings
DOI：https://doi.org/10.1109/MWSCAS48704.2020.9184700
DOI ID：10.1109/MWSCAS48704.2020.9184700, DBLP ID：conf/mwscas/ZhangSYS20 - Cross Conditional Network for Speech Enhancement
Haruki Tanaka; Yosuke Sugiura; Nozomiko Yasui; Tetsuya Shimamura; Ryoichi Miyazaki
2019 International Symposium on Intelligent Signal Processing and Communication Systems (ISPACS), First page：1, Last page：2, Dec. 2019, [Reviewed]
IEEE, English, International conference proceedings
DOI：https://doi.org/10.1109/ispacs48206.2019.8986375
DOI ID：10.1109/ispacs48206.2019.8986375, DBLP ID：conf/ispacs/TanakaSYSM19 - Convolutional Neural Network for Blind Image Quality Assessment
Khaing Yadanar; Sugiura Yosuke; Shimamura Tetsuya
Journal of Signal Processing, Volume：23, Number：6, First page：267, Last page：275, Nov. 2019, [Reviewed]
Blind image quality assessment (BIQA) methods can measure the quality of distorted images even without referencing the original images. This property is indispensable in the image processing field because reference images are normally not available in practice. Unlike the existing trained models, in our work, the training process is constructed as an end-to-end learning mechanism that minimizes the loss between the predicted score and the ground-truth score of the human vision system (HVS). Moreover, a convolutional neural network (CNN) takes distorted images as input and outputs the related score for each image. In this paper, we evaluate the proposed method on six publicly available benchmarks and the cross-database validation performance on the LIVE, CSIQ and TID2013 databases. The experimental results show that our proposed method outperforms other state-of-the-art methods.
Research Institute of Signal Processing, Japan, English, Scientific journal
DOI：https://doi.org/10.2299/jsp.23.267
DOI ID：10.2299/jsp.23.267, ISSN：1342-6230, eISSN：1880-1013, CiNii Articles ID：130007745926 - Blind Equalization Based on Normalized Error in Wireless Sensor Networks
Parvin Miss. Nargis; Sugiura Yosuke; Shimamura Tetsuya
Journal of Signal Processing, Volume：23, Number：5, First page：215, Last page：225, Sep. 2019, [Reviewed]
In this paper, we consider a single-input multiple-output (SIMO) channel-based static wireless sensor network and carry out blind equalization to estimate the transmitted signal blindly. Four cases of common or different channels and a common or different variance of noises are considered. For each case, the solution of blind equalization is derived. For the different-channel cases, we derive a new approach in which the best sensor output signal is found by adaptively implementing the normalized error used in speech processing. We estimate the transmitted signal from the corresponding sensor output by utilizing the generalized Sato equalizer. The mean square error (MSE) and symbol error rate (SER) are investigated on several communication channels. Computer simulations validate the solution for each case and show the effectiveness of the proposed method relative to the conventional methods.
Research Institute of Signal Processing, Japan, English, Scientific journal
DOI：https://doi.org/10.2299/jsp.23.215
DOI：https://doi.org/10.2299/jsp.27.35_references_DOI_QPWp1fLEgrswJbWJphb47ChtHP0
DOI ID：10.2299/jsp.23.215, ISSN：1342-6230, eISSN：1880-1013, CiNii Articles ID：130007706806 - Combination of Dissimilar Feature Scores for Image Quality Assessment Using Particle Swarm Optimization Algorithm
Khaing Yadanar; Sugiura Yosuke; Shimamura Tetsuya
Journal of Signal Processing, Volume：23, Number：5, First page：205, Last page：214, Sep. 2019, [Reviewed]
In this paper, we propose a new combination technique for full-reference image quality assessment (IQA) by utilizing three better-recognized IQA methods. To select the IQA methods, we first pick up Most Apparent Distortion (MAD) as the most appropriate IQA index for image quality databases and then add two other indices, MS-SSIM and FSIM, which have the most dissimilar features from the first index MAD. The parameter values employed in the new IQA score are optimized using the particle swarm optimization algorithm. By experiments, it is validated that the proposed method gives the best performance for various databases and outperforms the other state-of-the-art methods.
Research Institute of Signal Processing, Japan, English, Scientific journal
DOI：https://doi.org/10.2299/jsp.23.205
DOI ID：10.2299/jsp.23.205, ISSN：1342-6230, eISSN：1880-1013, CiNii Articles ID：130007706807 - Model-Based Vehicle Position Estimation Using Millimeter Wave Radar
Yoshihiro Suzuki; Yosuke Sugiura; Tetsuya Shimamura; Osamu Isaji; Kazuaki Hamada; Kazuhiko Shite
International Journal of Future Computer and Communication, Volume：8, Number：3, First page：94, Last page：98, Sep. 2019, [Reviewed]
EJournal Publishing, English, Scientific journal
DOI：https://doi.org/10.18178/ijfcc.2019.8.3.547
DOI ID：10.18178/ijfcc.2019.8.3.547, ISSN：2010-3751 - Angle Analysis and Blind Equalization in Wireless Sensor Networks
SuLin Chi; Nargis Parvin; Yosuke Sugiura; Nozomiko Yasui; Tetsuya Shimamura
2019 IEEE 2nd International Conference on Information Communication and Signal Processing (ICICSP), First page：102, Last page：106, Sep. 2019, [Reviewed]
International conference proceedings
DOI：https://doi.org/10.1109/icicsp48821.2019.8958528
DOI ID：10.1109/icicsp48821.2019.8958528, Web of Science ID：WOS:000516605600022 - Flexible Edge Component Detection Using Image Power Spectrum Sparsity
Nyunt Naw Jacklin; Sugiura Yosuke; Shimamura Tetsuya
Journal of Signal Processing, Volume：23, Number：4, First page：189, Last page：192, Jul. 2019, [Reviewed]
A novel method for edge component detection based on image power spectrum sparsity is presented. The edge size can be varied by changing the block size and threshold parameter to obtain the desired edge component. The image is first divided into sub-blocks and the power spectrum sparsity for each sub-block is calculated. On the basis of the image power spectrum sparsity value, each block is verified by the threshold value to determine the edge component. The experimental results show that the proposed method is suitable for object tracking because of the novel feature of the flexible edge size, which can dramatically reduce the amount of data to be stored.
Research Institute of Signal Processing, Japan, English, Scientific journal
DOI：https://doi.org/10.2299/jsp.23.189
DOI ID：10.2299/jsp.23.189, ISSN：1342-6230, eISSN：1880-1013, CiNii Articles ID：130007681744 - Noise Level Estimation on Weak-Texture Image Patch with Image Power Spectrum Sparsity
Nyunt Naw Jacklin; Sugiura Yosuke; Shimamura Tetsuya
Journal of Signal Processing, Volume：23, Number：3, First page：95, Last page：103, May 2019, [Reviewed]
Noise level estimation is important to improve the performance of different image-processing algorithms. Among the different noise level estimation methods, a block-based approach is one of the most effective approaches for estimating the noise level. A noise level estimation method based on a weak-texture patch using the image power spectrum sparsity in the frequency domain is proposed in this paper. A weaktexture image patch is first selected according to the value of image power spectrum sparsity. From the selected weak-texture image patch, the noise variance is estimated by selecting the frequency regions where the image frequency parts are not concentrated. It is observed that the proposed noise level estimation method is effective, especially for images with a rich texture. Furthermore, the proposed method provides a shorter computational time than the conventional methods.
Research Institute of Signal Processing, Japan, English, Scientific journal
DOI：https://doi.org/10.2299/jsp.23.95
DOI ID：10.2299/jsp.23.95, ISSN：1342-6230, eISSN：1880-1013, CiNii Articles ID：130007649794 - Live Demonstration of Reconstruction Filtering for Bone-Conducted Speech in High Noise
Yosuke Sugiura; Tetsuya Shimamura
2019 IEEE International Symposium on Circuits and Systems (ISCAS), First page：1, Last page：1, May 2019, [Reviewed], [Lead]
IEEE, English, International conference proceedings
DOI：https://doi.org/10.1109/iscas.2019.8702216
DOI ID：10.1109/iscas.2019.8702216 - Parametric Wiener Filter Based on Image Power Spectrum Sparsity
Nyunt Naw Jacklin; Sugiura Yosuke; Shimamura Tetsuya
Journal of Signal Processing, Volume：22, Number：6, First page：287, Last page：297, Nov. 2018, [Reviewed]
A simple and effective denoising method for a spectral subtractive (SS)-type parametric Wiener filter (PWF) for a blind condition is proposed. A simple noise estimation method is used to estimate the noise variance directly from a noisy image. Preliminary experiments with trained images are conducted to find the best parameters for the PWF. The PWF gives the highest performance with the best parameter setting. However, in practice, it is difficult to know the best parameters because they depend on the characteristics of the image. To estimate the best parameters for the PWF, therefore, a novel tool named image power spectrum sparsity, which is not influenced by the noise level, is derived. The parameters for the PWF are set according to the power spectrum sparsity. To demonstrate the effectiveness of the PWF, untrained images are used. The experimental results show that the proposed method gives a good performance with the shortest computational time among the WF methods to restore an image under a blind condition.
Research Institute of Signal Processing, Japan, English, Scientific journal
DOI：https://doi.org/10.2299/jsp.22.287
DOI：https://doi.org/10.2299/jsp.28.57_references_DOI_MfeYpKG9mYztieDZ0ACE9nANYuR
DOI ID：10.2299/jsp.22.287, ISSN：1342-6230, eISSN：1880-1013, CiNii Articles ID：130007521320 - Speech Enhancement Based on Sparse Representation in Logarithmic Frequency Scale
Yosuke Sugiura; Tetsuya Shimamura
2018 International Symposium on Intelligent Signal Processing and Communication Systems (ISPACS), First page：252, Last page：257, Nov. 2018, [Reviewed], [Lead]
IEEE, English, International conference proceedings
DOI：https://doi.org/10.1109/ispacs.2018.8923301
DOI ID：10.1109/ispacs.2018.8923301 - Adaptive-Normalized-Error Based Blind Equalization Algorithm for Static Wireless Sensor Network
Nargis Parvin; Yosuke Sugiura; Tetsuya Shimamura
First page：0503, Last page：0507, Oct. 2018, [Reviewed]
English, International conference proceedings
DOI：https://doi.org/10.1109/tencon.2018.8650288
DOI：https://doi.org/10.2299/jsp.23.243_references_DOI_XYEaFBMih3grP4xFa0m0POHyVOA
DOI ID：10.1109/tencon.2018.8650288 - Speech enhancement for bone-conducted speech based on low-order cepstrum restoration
Daiki Watanabe; Yosuke Sugiura; Tetsuya Shimamura; Hisanori Makinae
2017 International Symposium on Intelligent Signal Processing and Communication Systems (ISPACS), First page：212, Last page：216, Nov. 2017, [Reviewed]
IEEE, International conference proceedings
DOI：https://doi.org/10.1109/ispacs.2017.8266475
DOI ID：10.1109/ispacs.2017.8266475 - Parametric wiener filter with parameters estimation on image power spectrum sparsity
Naw Jacklin Nyunt; Yosuke Sugiura; Tetsuya Shimamura
2017 6th International Conference on Informatics, Electronics and Vision & 2017 7th International Symposium in Computational Medical and Health Technology (ICIEV-ISCMHT), First page：1, Last page：6, Sep. 2017, [Reviewed]
IEEE, English, International conference proceedings
DOI：https://doi.org/10.1109/iciev.2017.8338580
DOI ID：10.1109/iciev.2017.8338580 - Fundamental frequency estimation combining air-conducted speech with bone-conducted speech in noisy environment
Shiming Zhang; Yosuke Sugiura; Tetsuya Shimamura; Hisanori Makinae
2017 International Conference on Electrical, Computer and Communication Engineering (ECCE), First page：244, Last page：247, Feb. 2017, [Reviewed]
IEEE, English, International conference proceedings
DOI：https://doi.org/10.1109/ecace.2017.7912912
DOI ID：10.1109/ecace.2017.7912912 - Optimized three scores combination for image quality assessment
Kei Ishiyama; Yosuke Sugiura; Tetsuya Shimamura
2016 IEEE Asia Pacific Conference on Circuits and Systems (APCCAS), First page：5, Last page：8, Oct. 2016, [Reviewed]
IEEE, English, International conference proceedings
DOI：https://doi.org/10.1109/apccas.2016.7803881
DOI ID：10.1109/apccas.2016.7803881 - Fast and Accurate Monotonically Increasing Gradient Algorithm for Adaptive IIR Notch Filter
Yosuke Sugiura; Tetsuya Shimamura
IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences, Volume：J99-A, Number：10, First page：391, Last page：398, Oct. 2016, [Reviewed], [Lead]
Japanese, Scientific journal - Instantaneous frequency estimation for a sinusoidal signal combining DESA-2 and notch filter
Yosuke Sugiura; Keisuke Usukura; Naoyuki Aikawa
2015 23rd European Signal Processing Conference (EUSIPCO), First page：2676, Last page：2680, Aug. 2015, [Reviewed], [Lead]
IEEE, English, International conference proceedings
DOI：https://doi.org/10.1109/eusipco.2015.7362870
DOI ID：10.1109/eusipco.2015.7362870 - A general expression of the low-pass maximally flat FIR digital differentiators
Takashi Yoshida; Yosuke Sugiura; Naoyuki Aikawa
2015 IEEE International Symposium on Circuits and Systems (ISCAS), First page：2197, Last page：2200, May 2015, [Reviewed]
IEEE, English, International conference proceedings
DOI：https://doi.org/10.1109/iscas.2015.7169117
DOI ID：10.1109/iscas.2015.7169117 - Image Classification for Compositional Analysis of a Mixture of NdH and Fe(B) Phases
Ohta Keisuke; Sugiura Yosuke; Aikawa Naoyuki; Kumon Shouiti; Tamura Ryuji
The Journal of The Institute of Image Information and Television Engineers, Volume：68, Number：9, First page：J385, Last page：J390, Sep. 2014, [Reviewed]
近年，モータの省エネルギー化に向けて，永久磁石，とりわけNd-Fe-Bナノコンポジットバルク磁石の作製手法に関する研究が進められている．この作製手法の評価は，磁石や前駆体であるNdH/Fe(B)混相組織の組成分析に基づいている．また，目視観察による組成分析は，観察者に負担を伴うことが問題視されていた．そこで，本論文では画像処理による組成像の新たな領域分割，分類手法を提案する．はじめに，組成像に対し，輝度の極値を用いて，Watershedアルゴリズムによる領域分割を行い，3種類の領域に分類する．次に，領域分割時に発生する分割の誤りに対しては，領域の輝度分散を用いて再度領域分割を行い，過剰な領域分割に対しては，領域の統合を行う．また，実際にNdH/Fe(B)混相組織の組成像に本手法を適用し，提案法が閾値法や従来のWatershedアルゴリズムより目視観察に近い結果が得られることを示す．
The Institute of Image Information and Television Engineers, Japanese, Scientific journal
DOI：https://doi.org/10.3169/itej.68.j385
DOI ID：10.3169/itej.68.j385, ISSN：1342-6907, eISSN：1881-6908, CiNii Articles ID：130004678941 - A Closed-Form Design of Linear Phase FIR Band-Pass Maximally Flat Digital Differentiators with an Arbitrary Center Frequency
Takashi YOSHIDA; Yosuke SUGIURA; Naoyuki AIKAWA
IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences, Volume：E97.A, Number：12, First page：2611, Last page：2617, 2014, [Reviewed]
Institute of Electronics, Information and Communications Engineers (IEICE), English, Scientific journal
DOI：https://doi.org/10.1587/transfun.e97.a.2611
DOI ID：10.1587/transfun.e97.a.2611, ISSN：0916-8508, eISSN：1745-1337, CiNii Articles ID：130004706428 - A comb filter with adaptive notch bandwidth for periodic noise reduction
Yosuke Sugiura; Arata Kawamura; Naoyuki Aikawa
2013 9th International Conference on Information, Communications & Signal Processing, First page：1, Last page：4, Dec. 2013, [Reviewed], [Lead]
IEEE, English, International conference proceedings
DOI：https://doi.org/10.1109/icics.2013.6782856
DOI ID：10.1109/icics.2013.6782856 - An Adaptive Howling Canceller Using 2-Tap Linear Predictor
Akira Sogami; Yosuke Sugiura; Arata Kawamura; Youji Iiguni
Circuits and Systems, Volume：04, Number：01, First page：6, Last page：10, 2013, [Reviewed]
Scientific Research Publishing, Inc., English, Scientific journal
DOI：https://doi.org/10.4236/cs.2013.41002
DOI ID：10.4236/cs.2013.41002, ISSN：2153-1285, eISSN：2153-1293 - Performance Analysis of an Inverse Notch Filter and Its Application to F0 Estimation
Yosuke Sugiura; Arata Kawamura; Youji Iiguni
Circuits and Systems, Volume：04, Number：01, First page：117, Last page：122, 2013, [Reviewed], [Lead]
Scientific Research Publishing, Inc., English, Scientific journal
DOI：https://doi.org/10.4236/cs.2013.41017
DOI ID：10.4236/cs.2013.41017, ISSN：2153-1285, eISSN：2153-1293 - An Adaptive Comb Filter with Flexible Notch Gain
Yosuke SUGIURA; Arata KAWAMURA; Youji IIGUNI
IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences, Volume：E95.A, Number：11, First page：2046, Last page：2048, 2012, [Reviewed], [Lead]
Institute of Electronics, Information and Communications Engineers (IEICE), English, Scientific journal
DOI：https://doi.org/10.1587/transfun.e95.a.2046
DOI ID：10.1587/transfun.e95.a.2046, ISSN：0916-8508, eISSN：1745-1337, CiNii Articles ID：10031142613, CiNii Books ID：AA10826239 - A Comb Filter Design Method Using Linear Phase FIR Filter
Yosuke SUGIURA; Arata KAWAMURA; Youji IIGUNI
IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences, Volume：E95.A, Number：8, First page：1310, Last page：1316, 2012, [Reviewed], [Lead]
Institute of Electronics, Information and Communications Engineers (IEICE), English, Scientific journal
DOI：https://doi.org/10.1587/transfun.e95.a.1310
DOI ID：10.1587/transfun.e95.a.1310, ISSN：0916-8508, eISSN：1745-1337, CiNii Articles ID：10031126649, CiNii Books ID：AA10826239 - Design of an IIR comb filter with variable bandwidths
杉浦 陽介; 川村 新; 飯國 洋二
The IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences (Japanese edition). A, Volume：94-A, Number：1, First page：41, Last page：43, Jan. 2011, [Reviewed], [Lead]
Japanese, Scientific journal
ISSN：0913-5707, CiNii Articles ID：110008007082, CiNii Books ID：AN10013345
- ChatGPTを用いた対話型編曲システムに関する検討—A Study on an Interactive Arrangement System Using ChatGPT
原田 隼太朗; 杉浦 陽介; 安井 希子; 島村 徹也
Volume：43, Number：5, First page：7, Last page：9, Oct. 2024
Japanese
ISSN：0912-7283, CiNii Books ID：AN10170875 - グラフ信号処理を用いたエッジ抽出とその応用—Edge Extraction Using Graph Signal Processing and Its Applications—知覚情報/次世代産業システム合同研究会・センシング・画像・AI活用および処理一般
落合 亮; 杉浦 陽介; 島村 徹也
Volume：2024, Number：1-15, First page：23, Last page：28, 26 Mar. 2024
Japanese - Optimization of Video Denoising Method using Pixel Shuffle and FP16
益子陸; 杉浦陽介; 島村徹也
電子情報通信学会大会講演論文集(CD-ROM), Volume：2024, Feb. 2024
ISSN：1349-144X, J-Global ID：202402251379693790 - Performance Verification Using Computer Simulations of an Improved Hybrid ANC System for Uncorrelated Secondary Noise Sources
杉浦陽介; 滑川翔介; 島村徹也
電子情報通信学会技術研究報告(Web), Volume：124, Number：318(EA2024 64-76), 2024, [Lead]
ISSN：2432-6380, J-Global ID：202502235386560462 - 行動・姿勢指標を用いた豚の分娩検知精度の検討
石井彩夏; 江川紗智子; 徳永忠昭; 坂本信介; 右京里那; 橋本果林; 宮野大輝; 杉浦陽介; 平山祐理
Volume：121st, 2024
J-Global ID：202502224845926227 - 和音進行の出現確率を含むデータベースを用いた和音名推定の基礎的検討—A study of estimation of chord labels using a database containing occurrence probabilities of chord progressions
北条 拓巳; 村上 頌; 安井 希子; 三浦 雅展; 杉浦 陽介; 島村 徹也
Volume：41, Number：9, First page：25, Last page：28, 19 Feb. 2023
Japanese
ISSN：0912-7283, CiNii Books ID：AN10170875 - パターン情報の特徴を用いた自動伴奏生成に関する検討—A study of automatic accompaniment generation by using feature of pattern information
原田 隼太朗; 安井 希子; 杉浦 陽介; 三浦 雅展; 島村 徹也
Volume：41, Number：9, First page：71, Last page：76, 19 Feb. 2023
Japanese
ISSN：0912-7283, CiNii Books ID：AN10170875 - 非線形回帰分析を用いた歌唱のうまさに対する印象評価構造—Impression Evaluation Model using Nonlinear Regression Analysis for Goodness of Singing
新明 直斗; 安井 希子; 杉浦 陽介; 島村 徹也
Volume：41, Number：9, First page：47, Last page：50, 19 Feb. 2023
Japanese
ISSN：0912-7283, CiNii Books ID：AN10170875 - Investigation of introducing data augmentation methods to improve speech enhancement performance
春日玲人; 杉浦陽介; 安井希子; 島村徹也
電子情報通信学会技術研究報告(Web), Volume：122, Number：410(SIS2022 40-58), 2023
ISSN：2432-6380, J-Global ID：202302229931320529 - 印刷品質評価のための主観評価データセットの作成—Creation of subjective evaluation datasets for Print Quality Assessment—システム実現技術,近距離通信応用システム,知的マルチメディア処理システム,放送技術および一般
利根川 涼介; 杉浦 陽介; 安井 希子; 島村 徹也
Volume：46, Number：30, First page：37, Last page：42, Oct. 2022
Japanese
ISSN：1342-6893, CiNii Books ID：AN1059086X - スパース通信路に対するブラインド推定手法の検討—A Study of Blind Estimation for Sparse Channel for the Technical Report of the Institute of Electronics, Information and Communication Engineers Guide to the Technical Report and Template—システム実現技術,近距離通信応用システム,知的マルチメディア処理システム,放送技術および一般
杉浦 陽介; 篠田 開斗; 安井 希子; 島村 徹也
Volume：46, Number：30, First page：61, Last page：65, Oct. 2022, [Lead]
Japanese
ISSN：1342-6893, CiNii Books ID：AN1059086X - 音声自然性改善に向けた音声強調ネットワークに対するカプセル構造の導入—Toward Improving Speech Naturalness Introducing a Capsule Structure for Speech Enhancement Networks—システム実現技術,近距離通信応用システム,知的マルチメディア処理システム,放送技術および一般
春日 玲人; 島村 徹也; 杉浦 陽介; 安井 希子
Volume：46, Number：30, First page：15, Last page：20, Oct. 2022
Japanese
ISSN：1342-6893, CiNii Books ID：AN1059086X - 降水量に応じたACMによる高効率衛星通信—High efficient satellite communication with ACM complying with precipitation amount—システム実現技術,近距離通信応用システム,知的マルチメディア処理システム,放送技術および一般
宮本 周; 杉浦 陽介; 安井 希子; 島村 徹也
Volume：46, Number：30, First page：55, Last page：59, Oct. 2022
Japanese
ISSN：1342-6893, CiNii Books ID：AN1059086X - Automatic Modulation Classification Based on SNR Estimation Using Multi-Task Learning
町田航; 杉浦陽介; 安井希子; 島村徹也
電子情報通信学会技術研究報告(Web), Volume：121, Number：327(IT2021 28-82), 2022
ISSN：2432-6380, J-Global ID：202202221920615295 - アテンション機構による音声強調ネットワークの性能改善—Performance improvement of speech enhancement network using attention-mechanism—システム研究会 ディジタル信号処理システム一般
杉浦 陽介
Volume：2021, Number：1-6, First page：1, Last page：4, 23 Apr. 2021, [Lead]
Japanese
CiNii Articles ID：40022555679 - Optimization of source-filter based speech waveform generation using adversarial training
光井勇人; 杉浦陽介; 安井希子; 島村徹也
電子情報通信学会技術研究報告(Web), Volume：120, Number：415(SIS2020 35-59), 2021
ISSN：2432-6380, J-Global ID：202102234330010696 - Adversarial Training using Self-Attention Architecture for Speech Enhancement Network
杉浦陽介; 島村徹也
電子情報通信学会技術研究報告, Volume：119, Number：458(SIS2019 37-60), First page：125, Last page：129, 2020, [Lead]
Japanese
ISSN：0913-5685, J-Global ID：202002277013145259, CiNii Articles ID：40022208412, CiNii Books ID：AA1123312X - Adversarial Learning Architecture Based on Edge Information for Image Completion Network
森康一; 杉浦陽介; 安井希子; 島村徹也
電子情報通信学会技術研究報告, Volume：119, Number：458(SIS2019 37-60), First page：131, Last page：135, 2020
Japanese
ISSN：0913-5685, J-Global ID：202002213824888445, CiNii Articles ID：40022208416, CiNii Books ID：AA1123312X - Performance improvement of speech enhancement network by multitask learning including noise information
田中 晴樹; 杉浦 陽介; 安井 希子; 島村 徹也; 宮崎 亮一
Volume：119, Number：334, First page：31, Last page：36, 12 Dec. 2019
Japanese
ISSN：0913-5685, CiNii Articles ID：40022117915, CiNii Books ID：AN10164817 - サブバンド分解を用いたk-SVDに基づく画像雑音除去—Image Denoising based on k-SVD using Sub-band decomposition—システム研究会 ディジタル信号処理システム最適化一般
杉浦 陽介; 池上 征人; 島村 徹也
Volume：2019, Number：12-18, First page：33, Last page：38, 14 Jun. 2019, [Lead]
Japanese
CiNii Articles ID：40022004967, CiNii Books ID：AA12505509 - 潜在変数のスパース化によるSEGANの雑音抑圧性能の改善
佐久間南海; 杉浦陽介; 島村徹也
Volume：2019, 2019
ISSN：1880-7658, J-Global ID：201902262255165557 - MIMOにおける雑音分散を考慮したQRM-MLD法の性能改善—Improvement of QRM-MLD Method for MIMO Utilizing Noise Variance
今野 遼太郎; 杉浦 陽介; 島村 徹也
Volume：117, Number：482, First page：51, Last page：56, Mar. 2018
Japanese
ISSN：0913-5685, CiNii Articles ID：40021522621, CiNii Books ID：AA1123312X - 窓なし重み付き自己相関関数を用いた基本周波数推定—Pitch Estimation Using Windowless Weighted Auto-Correlation Function
三谷 恭平; 杉浦 陽介; 島村 徹也
Volume：117, Number：482, First page：7, Last page：12, Mar. 2018
Japanese
ISSN：0913-5685, CiNii Articles ID：40021522425, CiNii Books ID：AA1123312X - Non-Local Meansを用いた音声強調—Speech Enhancement Using Non-Local Means
三谷 恭平; 杉浦 陽介; 島村 徹也
Volume：117, Number：517, First page：227, Last page：230, Mar. 2018
Japanese
ISSN：0913-5685, CiNii Articles ID：40021521738, CiNii Books ID：AA1123312X - A Study on Structure of Deep Neural Network for Speech Enhancement
杉浦陽介; 島村徹也
電子情報通信学会技術研究報告, Volume：117, Number：516(SIP2017 111-184), First page：379, Last page：384, 2018, [Lead]
Japanese
ISSN：0913-5685, J-Global ID：201802227684981000, CiNii Articles ID：40021523662, CiNii Books ID：AA1123312X - Voiceless Consonant Detection and Artificial Bandwidth Extension of Narrow Band Speech
浅和駿; 杉浦陽介; 島村徹也
電子情報通信学会技術研究報告, Volume：117, Number：516(SIP2017 111-184), First page：231, Last page：234, 2018
Japanese
ISSN：0913-5685, J-Global ID：201802254828644723, CiNii Articles ID：40021521744, CiNii Books ID：AA1123312X - Introduction to Speech Enhancement
杉浦陽介
電気学会システム研究会資料, Volume：2017, Number：21-37, First page：5, Last page：9, 16 Sep. 2017, [Lead]
Japanese
J-Global ID：201702244508177258, CiNii Articles ID：40021339455, CiNii Books ID：AA12505509 - モフォロジカルフィルタによる雑音スペクトル推定に基づく風雑音除去
CAI Chengkai; 服部新栄; 中静真; 杉浦陽介
Volume：2017, 2017
ISSN：1349-144X, J-Global ID：201702225097304517 - ポスター講演 雑音に頑強な話者認識のための基本周波数を用いた深層ニューラルネットワーク—Poster Presentation : Deep Neural Network Using Fundamental Frequency For Noise Robust Speaker Recognition—音声 ; 第18回音声言語シンポジウム
鈴木 良啓; 杉浦 陽介; 島村 徹也
Volume：116, Number：378, First page：53, Last page：56, Dec. 2016
Japanese
ISSN：0913-5685, CiNii Articles ID：40021060166, CiNii Books ID：AA1123312X - スペクトル包絡と無声子音情報を利用する狭帯域音声の帯域拡張—Artificial Bandwidth Extension of Narrow Band Speech Using Spectral Envelope and Voiceless Consonant Information—応用音響
浅和 駿; 杉浦 陽介; 島村 徹也
Volume：116, Number：122, First page：57, Last page：62, Jul. 2016
Japanese
ISSN：0913-5685, CiNii Articles ID：40020906811, CiNii Books ID：AA1123312X - シンボルインタリーブによるUWB通信における狭帯域干渉軽減—Narrowband Interference Mitigation via Symbol Interleaving for UWB Communication Systems
小川 永策; 杉浦 陽介; 島村 徹也
Volume：115, Number：505, First page：129, Last page：134, Mar. 2016
Japanese
ISSN：0913-5685, CiNii Articles ID：40020801903, CiNii Books ID：AA1123312X - 畳み込みニューラルネットワークを用いた音声強調
杉浦陽介; 島村徹也
Volume：31st, 2016, [Lead]
J-Global ID：201602276994836764 - べき乗振幅スペクトルのDCT解析に基づくピッチ抽出
杉浦陽介; 島村徹也
Volume：2016, 2016, [Lead]
ISSN：1349-144X, J-Global ID：201602249923738710 - Adding Phase Information to Cross-Correlation Functions with Binary Signal for Speech Enhancement
三谷恭平; 杉浦陽介; 島村徹也
電子情報通信学会技術研究報告, Volume：116, Number：122(EA2016 7-19), First page：63, Last page：68, 2016
Japanese
ISSN：0913-5685, J-Global ID：201602254273875216, CiNii Articles ID：40020906823, CiNii Books ID：AA1123312X - D-14-2 Howling Canceler Using an Adaptive Notch Filter with Flexible Gain
MASHITA Kanji; UEHARA Yuki; SUGIURA Yosuke; AIKAWA Naoyuki
Proceedings of the IEICE General Conference, Volume：2015, Number：1, First page：164, 24 Feb. 2015
The Institute of Electronics, Information and Communication Engineers, Japanese
CiNii Articles ID：110009944949, CiNii Books ID：AN10471452 - 逆ノッチフィルタを用いた倍音構造に基づく音高推定システムの開発—A Pitch Detection System Based On Harmonic Structure Using The Inverse Notch Filter—制御研究会 制御工学分野における信号処理技術,および制御・信号処理一般
難波 慎太郎; 杉浦 陽介; 相川 直幸
Volume：2015, Number：4-19, First page：11, Last page：16, 28 Jan. 2015
Japanese
CiNii Articles ID：40020341263, CiNii Books ID：AA1250551X - ガボールフィルタを用いた特徴量空間による血液細胞分類システムの開発—Development of Hemocyte classification System Using Features Space Extracted by Gabor Filter—制御研究会 制御工学分野における信号処理技術,および制御・信号処理一般
友田 哲平; 杉浦 陽介; 相川 直幸
Volume：2015, Number：4-19, First page：51, Last page：54, 28 Jan. 2015
Japanese
CiNii Articles ID：40020341492, CiNii Books ID：AA1250551X - フィードバックANCシステムの適応ノッチフィルタによる高速低演算量化—Feedback ANC System with Low Complexity Using Adaptive Notch Filters—制御研究会 制御工学分野における信号処理技術,および制御・信号処理一般
高橋 三記; 杉浦 陽介; 相川 直幸
Volume：2015, Number：4-19, First page：83, Last page：88, 28 Jan. 2015
Japanese
CiNii Articles ID：40020341720, CiNii Books ID：AA1250551X - Howling Canceler Using an Adaptive Notch Filter with Flexible Gain Which Has High Estimation Accuracy and Speech Quality
間下 寛二; 上原 裕貴; 杉浦 陽介
Volume：2015, Number：4, First page：29, Last page：34, 28 Jan. 2015
Japanese
CiNii Articles ID：40020341356, CiNii Books ID：AA1250551X - An Accelerated Design of FIR Filters with CSD Coefficient Based on Branch and Bound Method Using GPU
大島純; 杉浦陽介; 相川直幸
電子情報通信学会技術研究報告, Volume：114, Number：395(RCS2014 269-300), 2015
ISSN：0913-5685, J-Global ID：201502210403346687 - Development of Hemocyte classification System Using Features Space Extracted by Gabor Filter
友田哲平; 杉浦陽介; 相川直幸
電気学会制御研究会資料, Volume：CT-15, Number：4-19, 2015
J-Global ID：201502258640454705 - A Pitch Detection System Based On Harmonic Structure Using The Inverse Notch Filter
難波慎太郎; 杉浦陽介; 相川直幸
電気学会制御研究会資料, Volume：CT-15, Number：4-19, 2015
J-Global ID：201502270305497157 - 等リプルな阻止域を有する直線位相帯域通過FIR最大平たんディジタル微分器の一設計法
吉田嵩; 杉浦陽介; 相川直幸
Volume：J98-A, Number：7, 2015
ISSN：1881-0195, J-Global ID：201502213669274460 - FPGAを用いたおしぼり表面に付着した髪の毛の自動判別システムの開発—A Development of Automatic Discrimination System of Hair on the Wet Towel Using FPGA—信号処理
櫻田 大樹; 田中 稜介; 杉浦 陽介
Volume：114, Number：394, First page：109, Last page：112, Jan. 2015
Japanese
ISSN：0913-5685, CiNii Articles ID：110010001730, CiNii Books ID：AA1123312X - CSD係数FIRフィルタ設計における分枝限定法のGPUを用いた高速化に関する一検討—An Accelerated Design of FIR Filters with CSD Coefficient Based on Branch and Bound Method Using GPU—無線通信システム
大島 純; 杉浦 陽介; 相川 直幸
Volume：114, Number：395, First page：113, Last page：116, Jan. 2015
Japanese
ISSN：0913-5685, CiNii Articles ID：110010001731, CiNii Books ID：AA1123312X - 電気回路E-ラーニングの学習者支援インターフェース強化—Reinforcement of learner support interface in the electric circuit E-learning system—教育フロンティア研究会 技術者倫理と教育一般
髙橋 侑也; 杉浦 陽介; 相川 直幸
Volume：2014, Number：18・19・21-24, First page：5, Last page：9, 05 Sep. 2014
Japanese
CiNii Articles ID：40020225002, CiNii Books ID：AA11753039 - 適応ノッチフィルタを用いた音声解析に基づく複数のハウリングに対する抑圧システム—Suppression System for Multiple Howling Signal Based on Analyzing Speech Signal Using Adaptive Notch Filters
上原 裕貴; 杉浦 陽介; 相川 直幸
Volume：27, First page：179, Last page：184, Aug. 2014
Japanese
CiNii Articles ID：40020153205 - 単調増加勾配を用いた適応ノッチフィルタの周波数推定精度の改善—Improvement of Frequency Estimation Accuracy in Adaptive Notch Filter Using Monotonically Increasing Gradient
杉浦 陽介
Volume：27, First page：209, Last page：212, Aug. 2014, [Lead]
Japanese
J-Global ID：202102249521624718, CiNii Articles ID：40020153280 - 遅延の小さい低域通過FIRディジタル微分器の一設計法—A design method of lowpass FIR digital differentiators with reduced delay—信号処理
吉田 嵩; 杉浦 陽介; 相川 直幸
Volume：114, Number：124, First page：243, Last page：246, Jul. 2014
Japanese
ISSN：0913-5685, CiNii Articles ID：110009946155, CiNii Books ID：AA1123312X - 1次元トップハット変換を用いたスペクトルサブトラクション法に基づく風雑音抑圧—A Wind Noise Suppression Based on Spectral Subtraction Using One Dimensional Top-Hat Transform
杉浦 陽介; 相川 直幸
Volume：114, Number：126, First page：247, Last page：252, Jul. 2014, [Lead]
Japanese
ISSN：0913-5685, CiNii Articles ID：110009946156, CiNii Books ID：AA1123312X - 阻止域にリプルを持つFIRディジタル帯域通過最大平たん微分器の一設計法—A design method of FIR band-pass maximally flat digital differentiators having ripple in the stopband—回路とシステム
吉田 嵩; 杉浦 陽介; 相川 直幸
Volume：113, Number：463, First page：145, Last page：149, Mar. 2014
Japanese
ISSN：0913-5685, CiNii Articles ID：110009862152, CiNii Books ID：AA1123312X - Designing Maximally Flat Stopband FIR Notch Filter for Narrowband Radio Systems
重岩祐介; 杉浦陽介; 相川直幸; 伊丹誠
電子情報通信学会技術研究報告, Volume：113, Number：385(SIP2013 85-135), 2014
ISSN：0913-5685, J-Global ID：201402232105759061 - 電気回路E-ラーニングシステムにおける学習者支援インターフェースの強化
高橋侑也; 杉浦陽介; 相川直幸
Volume：2014, 2014
J-Global ID：201402238558771044 - IIRノッチフィルタを用いた狭帯域雑音の高速能動的制御システムの開発
高橋三記; 杉浦陽介; 相川直幸
Volume：2014, 2014
J-Global ID：201402259562121337 - Reinforcement of learner support interface in the electric circuit E-learning system
高橋郁也; 杉浦陽介; 相川直幸
電気学会教育フロンティア研究会資料, Volume：FIE-14, Number：18-19.21-24, 2014
J-Global ID：201402224555119680 - ガボールフィルタにより抽出した特徴量空間を用いた血液細胞解析システムの開発
友田哲平; 杉浦陽介; 相川直幸; 青木伸; 安盛敦雄
Volume：2014, 2014
ISSN：1880-6953, J-Global ID：201502216154517415 - 適応ノッチフィルタを用いた音声解析に基づく複数のハウリングに対する抑圧システム
上原裕貴; 杉浦陽介; 相川直幸
Volume：27, 2014
J-Global ID：202102262152661479 - 6-8 Development of Hemocyte Analysis System Using Features Space Extracted by Gabor Filter
TOMODA Teppei; SUGIURA Yosuke; AIKAWA Naoyuki; AOKI Shin; YASUMORI Atsuo
PROCEEDINGS OF THE ITE WINTER ANNUAL CONVENTION, Volume：2014, First page：6-8-1_, Last page：_6-8-1_, 2014
The Institute of Image Information and Television Engineers, Japanese
DOI：https://doi.org/10.11485/itewac.2014.0_6-8-1_
DOI ID：10.11485/itewac.2014.0_6-8-1_, ISSN：1343-4357, eISSN：2424-2306, CiNii Articles ID：110009933718 - 狭帯域無線システムのための阻止域最大平たんFIRノッチフィルタの設計—Designing Maximally Flat Stopband FIR Notch Filter for Narrowband Radio Systems—無線通信システム
重岩 祐介; 杉浦 陽介; 相川 直幸
Volume：113, Number：386, First page：223, Last page：228, Jan. 2014
Japanese
ISSN：0913-5685, CiNii Articles ID：110009825539, CiNii Books ID：AA1123312X - 適応ノッチフィルタを用いた音声解析に基づくハウリングキャンセラ
上原,裕貴; 杉浦,陽介; 相川,直幸
Volume：113, Number：464, First page：41, Last page：45, 2014
Japanese
ISSN：0913-5685, CiNii Articles ID：110009862134, CiNii Books ID：AA1123312X - 任意の周波数ゲインをもつくし型フィルタ—A Comb Filter with Desired Frequency Gains—基礎信号処理
杉浦 陽介; 川村 新; 飯國 洋二
Volume：24, First page：338, Last page：343, Aug. 2011, [Lead]
Japanese
CiNii Articles ID：40019430874 - Design of a Comb Filter with Desired Frequency Gains
杉浦陽介; 川村新; 飯國洋二
電子情報通信学会技術研究報告, Volume：111, Number：26, First page：149, Last page：154, May 2011, [Lead]
Japanese
ISSN：0913-5685, J-Global ID：201102280276759240, CiNii Articles ID：110008725585, CiNii Books ID：AA1123312X - A-4-45 Evaruation of a howling canceller using IIR comb filter
Sugiura Yosuke; Kawamura Arata; Iiguni Youji
Proceedings of the Society Conference of IEICE, Volume：2009, First page：108, 01 Sep. 2009, [Lead]
The Institute of Electronics, Information and Communication Engineers, Japanese
CiNii Articles ID：110007881421, CiNii Books ID：AN10489017 - A new howling canceller using IIR comb filter
Sugiura Yousuke; Kawamura Arata; Iiguni Youji
Proceedings of the Annual Conference of the Institute of Systems, Control and Information Engineers, Volume：SCI09, First page：643, Last page：643, 2009, [Lead]
ハウリングはスピーカ・マイクロホン間の閉ループにおいて，位相条件と振幅条件が満たされた場合に生じる共振現象である．従来法では，ハウリングの位相条件が，スピーカ-マイクロホン間の距離に依存して決まることに着目し，距離推定により得られた複数のハウリング周波数の候補を，縦続接続型ノッチフィルタにより除去する．しかし，従来法では演算量が多く，さらに隣接するフィルタの除去帯域が重複するため，出力音質が大きく劣化するという問題もある．そこで本稿では，比較的演算量の少ないIIRくし型フィルタを用いたハウリングキャンセラを提案する．IIRくし型フィルタは，隣接する除去帯域が重複しないように設計できるので，出力音質の劣化を抑えることができる．実環境における実験結果から，提案法が従来法よりも優れたハウリング除去性能を有することを明らかにする．
The Institute of Systems, Control and Information Engineers
DOI：https://doi.org/10.11509/sci.sci09.0.643.0
DOI ID：10.11509/sci.sci09.0.643.0, CiNii Articles ID：130006984392
- ディジタル信号処理におけるシステム最適化技術 : 基礎技術から音声・音響信号処理, 産業応用と情報システムまで
電気学会・ディジタル信号処理システム最適化技術調査専門委員会, [Joint work]
Oct. 2021
Japanese, Total pages：xiii, 263p, 図版 [2] p
CiNii Books：http://ci.nii.ac.jp/ncid/BC10771945
ISBN：9784274227608, CiNii Books ID：BC10771945
- THE INSTITUTE OF ELECTRICAL ENGINEERS OF JAPAN
- THE INSTITUTE OF ELECTRONICS, INFORMATION AND COMMUNICATION ENGINEERS
- IEEE
- Speech Enhancement Network using Perceptual and Physical Mathematical Model
Japan Society for the Promotion of Science, Grants-in-Aid for Scientific Research, Grant-in-Aid for Scientific Research (C), 01 Apr. 2021 - 31 Mar. 2024
Saitama University
Grant amount(Total)：2990000, Direct funding：2300000, Indirect funding：690000
Grant number：21K11953 - Development of Speech Enhancement Algorithm on Highly Noisy Environment Using Noise Database
Japan Society for the Promotion of Science, Grants-in-Aid for Scientific Research, Grant-in-Aid for Young Scientists (B), 01 Apr. 2016 - 31 Mar. 2018
SUGIURA Yosuke, Saitama University
Grant amount(Total)：1300000, Direct funding：1000000, Indirect funding：300000
We proposed accurate analysis methods for speech and and a speech enhancement architecture using deep neural network (DNN) in order to develop a speech enhancement algorithm on highly noisy environment. The former is an method to estimate the speech and noise accurately from the noisy speech including the non-stationary noise. The latter is designed analytically so as to be a structure matching the speech enhancement. They are expected to be important techniques in the environment affected by noise, such as the hands-free speech communication or the speech recognition on the AI speaker.
Grant number：16K18111