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2015 International Conference on Innovations in Information, Embedded and Communication Systems (ICIIECS)

作者： Imsiya, K. A. Nandana, B. T. RCET Dept ECE Akkikavu Thrissur India

ISBN: (纸本)9781479968183

A new blind speech extraction method consisting of a minimum mean-square error short-time spectral amplitude ( MMSE STSA) estimator and noise estimation based on independent component analysis ( ICA) is proposed in this paper. First, a computer simulation is performed using the artificial noise whose stationarity could be controlled parametrically and the obtained results indicate that the proposed method is superior to conventional methods such as blind spatial subtraction array ( BSSA) and the original MMSE STSA estimator under the non-point-source and nonstationary noise condition.

关键词： Blind source separation microphone array signal processing independent component analysis spectral subtraction MMSE STSA estimator

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Numerical Synthesis of an Optimal Low-Sidelobe Beam Pattern for a microphone array

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IEEE signal processing LETTERS 2014年第8期21卷 914-917页

作者： Hur, Yoomi Park, Young-Cheol Abel, Jonathan S. Youn, Dae Hee Stanford Univ Dept Mus CCRMA Stanford CA 94230 USA Yonsei Univ DSP Lab Dept Elect & Elect Engn Seoul 120749 South Korea Yonsei Univ Comp & Telecommun Engn Div Wonju South Korea

This letter describes a numerical algorithm for synthesizing optimal low-sidelobe beampatterns. The pattern synthesis problem is formulated as a constrained optimization that minimizes the spatially weighted energy arriving at the array subject to unit gain in the look direction and a constant sidelobe level. The weighting takes on the form of a sensor correlation matrix, parameterized between uncorrelated sensor noise and correlated signal arrival terms according to a balancing factor. Setting the balancing factor to its extreme values of 0 and 1, produces, respectively, the optimal Riblet-Chebyshev and Delay-and-Sum type beamformers. In between, the method generates a low-sidelobe beamformer with varying beamwidths that provides a trade-off between White Noise Gain and Directivity Index. Simulation examples demonstrate optimal and intermediate designs for uniform and non-uniform sensor spacings.

关键词： Beam pattern synthesis microphone array signal processing optimal beamforming

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DOA ESTIMATION OF SPEECH SOURCE IN NOISY ENVIRONMENTS WITH WEIGHTED SPATIAL BISPECTRUM CORRELATION MATRIX

DOA ESTIMATION OF SPEECH SOURCE IN NOISY ENVIRONMENTS WITH W...

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IEEE International Conference on Acoustics, Speech and signal processing (ICASSP)

作者： Xue, Wei Liang, Shan Liu, Wenju Chinese Acad Sci Inst Automat Natl Lab Pattern Recognit Beijing 100190 Peoples R China

ISBN: (纸本)9781479928934

Although the high order statistics (HOS) has promising property against the Gaussian noise, there still lack effective ways to apply the HOS to DOA estimation of the speech source. In this paper, we propose a novel HOS based DOA estimation method for speech source in strong noise conditions. A "weighted spatial bispectrum correlation matrix (WSBCM)" is formulated, which contains the spatial correlation information of bispectrum phase differences. We then propose a new DOA estimator based on the eigenvalue analysis of the WSBCM. Besides the theoretical advantage of the bispectrum against Gaussian noises, the redundant information in the bispectrum domain is also exploited to make the WSBCM noise robust. The WSBCM enables bispectrum weighting to select the speech units in the bispectrum, which further helps to improve the performance. Experimental results demonstrate that the proposed method outperforms existing algorithms in different kinds of noisy environments.

关键词： direction of arrival estimation microphone array signal processing bispectrum

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Novel Application of Spherical microphone array Sensor with Three-Dimensional Directivity for Home and Office Environments

Novel Application of Spherical Microphone Array Sensor with ...

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International Conference on Sensing Technology

作者： Takahiro Nakadai Ryuichi Yoshida Tomoki Taguchi Hiroshi Mizoguchi Etsuji Yamaguchi Shigenori Inagaki Yoshiaki Takeda Masanori Sugimoto Ryohei Egusa Miki Namatame Fusako Kusunoki Department of Mechanical Engineering Tokyo University of Science Graduate School of Human Development and Environment Kobe University Graduate School of Information Science and Technology Hokkaido University Faculty of Industrial Technology Tsukuba University of Technology Department of Information Design Tama Art University

ISBN: (纸本)9781479963157

Interest in sound interfaces is increasing because such interfaces do not need advanced knowledge about particular devices, nor do they require physical operation. However, such interfaces are difficult to use because the general living environment often contains background noise. In order to solve this problem, sound separation systems that use a microphone array sensor have been proposed. In previous work, this microphone array sensor was a small system that considered only two-dimensional (2-D) directivity control. In this paper, we present the design of a spherical microphone array sensor with 3-D directivity. This 3-D directivity property is confirmed via an experimental evaluation.

关键词： Delay and Sum Beamforming microphone array signal processing Sound Separation System

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Real-Time Multiple Sound Source Localization and Counting Using a Circular microphone array

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IEEE TRANSACTIONS ON AUDIO SPEECH AND LANGUAGE processing 2013年第10期21卷 2193-2206页

作者： Pavlidi, Despoina Griffin, Anthony Puigt, Matthieu Mouchtaris, Athanasios Inst Comp Sci FORTH ICS Fdn Res & Technol Hellas GR-70013 Iraklion Crete Greece Univ Crete Dept Comp Sci GR-70013 Iraklion Crete Greece

In this work, a multiple sound source localization and counting method is presented, that imposes relaxed sparsity constraints on the source signals. A uniform circular microphone array is used to overcome the ambiguities of linear arrays, however the underlying concepts (sparse component analysis and matching pursuit-based operation on the histogram of estimates) are applicable to any microphone array topology. Our method is based on detecting time-frequency (TF) zones where one source is dominant over the others. Using appropriately selected TF components in these "single-source" zones, the proposed method jointly estimates the number of active sources and their corresponding directions of arrival (DOAs) by applying a matching pursuit-based approach to the histogram of DOA estimates. The method is shown to have excellent performance for DOA estimation and source counting, and to be highly suitable for real-time applications due to its low complexity. Through simulations (in various signal-to-noise ratio conditions and reverberant environments) and real environment experiments, we indicate that our method outperforms other state-of-the-art DOA and source counting methods in terms of accuracy, while being significantly more efficient in terms of computational complexity.

关键词： Direction of arrival estimation matching pursuit microphone array signal processing multiple source localization real-time localization source counting sparse component analysis

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Interference Robust DOA Estimation of Human Speech by Exploiting Historical Information and Temporal Correlation

Interference Robust DOA Estimation of Human Speech by Exploi...

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14th Annual Conference of the International-Speech-Communication-Association (INTERSPEECH 2013)

作者： Xue, Wei Liang, Shan Liu, Wenju Chinese Acad Sci Natl Lab Pattern Recognit Inst Automat Beijing 100190 Peoples R China

ISBN: (纸本)9781629934433

Although various DOA estimation methods for human speech have been presented, most of them assume noises received by different microphones are undirected. However, strong directional interferences often also exist in practical scenarios and the performances of existing methods degrade seriously in such case. In this paper, we present a new interference robust DOA estimation method for human speech. Historical information and temporal correlation are taken advantage to deal with the problem. Firstly, utilizing the historical DOA estimates, we perform "post-beamforming" in the last frame to suppress the directional interferences. Then exploiting temporal correlation of speech spectra, frequency weights which highlight the effects of speech frequency bins are calculated based on the estimated a priori SNR of enhanced signal. Finally, we propose a new DOA cost function using frequency-weighted spatial correlation matrix to estimate the DOA of speech source. Experimental results show that the proposed method outperforms existing algorithms in reverberant environments with additive white Gaussian noises in the presence of different kinds of interferences.

关键词： direction of arrival estimation microphone array signal processing directional noise

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Wide-band dereverberation method based on multichannel linear prediction using prewhitening filter

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APPLIED ACOUSTICS 2012年第1期73卷 50-55页

作者： Okamoto, Takuma Iwaya, Yukio Suzuki, Yoiti Tohoku Univ Res Inst Elect Commun Aoba Ku Sendai Miyagi 9808577 Japan Tohoku Univ Grad Sch Engn Aoba Ku Sendai Miyagi 9808577 Japan Tohoku Univ Grad Sch Informat Sci Aoba Ku Sendai Miyagi 9808577 Japan

Several dereverberation algorithms have been studied. The sampling frequencies used in conventional studies are typically 8-16 kHz because their main purpose is preprocessing for improving the intelligibility of speech communication and articulation for automatic speech recognition. However, in next-generation communication systems, techniques to analyze and reproduce not only semantic information of sound but also more high-definition components such as spatial information and directivity will be increasingly necessary. To decompose these sound field characteristics with high definition, a dereverberation algorithm that is useful at high sampling frequencies is an important technique to process sound that includes high-frequency spectra such as musical sounds. The LInear-predictive Multichannel Equalization (LIME) algorithm is a promising dereverberation method. Using the LIME algorithm, however, a dereverberation signal cannot be solved at high sampling frequencies when the source signal is colored, such as in the case of speech and sound of musical signals. Because the rank of the correlation matrix calculated from such a colored signal is not full, the characteristic polynomial cannot be calculated precisely. To alleviate this problem, we propose preprocessing of all input signals with filters to whiten their spectra so that this algorithm can function for colored signals at high sampling frequencies. (C) 2011 Elsevier Ltd. All rights reserved.

关键词： microphone array signal processing Dereverberation LIME algorithm Colored source signal Prewhitening filter

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Speech Enhancement With a GSC-Like Structure Employing Eigenvector-Based Transfer Function Ratios Estimation

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IEEE TRANSACTIONS ON AUDIO SPEECH AND LANGUAGE processing 2011年第1期19卷 206-219页

作者： Krueger, Alexander Warsitz, Ernst Haeb-Umbach, Reinhold Univ Paderborn Dept Commun Engn D-33098 Paderborn Germany

In this paper, we present a novel blocking matrix and fixed beamformer design for a generalized sidelobe canceler for speech enhancement in a reverberant enclosure. They are based on a new method for estimating the acoustical transfer function ratios in the presence of stationary noise. The estimation method relies on solving a generalized eigenvalue problem in each frequency bin. An adaptive eigenvector tracking utilizing the power iteration method is employed and shown to achieve a high convergence speed. Simulation results demonstrate that the proposed beamformer leads to better noise and interference reduction and reduced speech distortions compared to other blocking matrix designs from the literature.

关键词： Acoustical transfer function ratios generalized eigenvalue problem generalized sidelobe canceler (GSC) microphone array signal processing speech enhancement

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MMSE STSA ESTIMATOR WITH NONSTATIONARY NOISE ESTIMATION BASED ON ICA FOR HIGH-QUALITY SPEECH ENHANCEMENT

MMSE STSA ESTIMATOR WITH NONSTATIONARY NOISE ESTIMATION BASE...

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2010 IEEE International Conference on Acoustics, Speech, and signal processing

作者： Okamoto, Ryoi Takahashi, Yu Saruwatari, Hiroshi Shikano, Kiyohiro Nara Inst Sci & Technol Grad Sch Informat Sci Ikoma Nara 6300192 Japan

ISBN: (纸本)9781424442966

In this paper, we propose a new blind speech extraction method consisting of a minimum mean-square error short-time spectral amplitude (MMSE STSA) estimator and noise estimation based on independent component analysis (ICA). First, we perform a computer simulation using the artificial noise whose stationarity could be controlled parametrically, and the obtained results indicate that the proposed method is superior to conventional methods, such as blind spatial subtraction array (BSSA) and the original MMSE STSA estimator under the non-point-source and nonstationary noise condition. Finally, we conduct an experiment in an actual railway-station environment, and objective and subjective evaluations to confirm the advantage of the proposed method in the real world.

关键词： Blind source separation microphone array signal processing independent component analysis spectral subtraction MMSE STSA estimator

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MMSE STSA ESTIMATOR WITH NONSTATIONARY NOISE ESTIMATION BASED ON ICA FOR HIGH-QUALITY SPEECH ENHANCEMENT

MMSE STSA ESTIMATOR WITH NONSTATIONARY NOISE ESTIMATION BASE...

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IEEE International Conference on Acoustics, Speech, and signal processing

作者： Ryoi Okamoto Yu Takahashi Hiroshi Saruwatari Kiyohiro Shikano Graduate School of Information Science Nara Institute of Science and Technology 8916-5 Takayama-cho Ikoma-shi Nara 630-0192 JAPAN

ISBN: (纸本)9781424442959

关键词： Blind source separation microphone array signal processing independent component analysis spectral subtraction MMSE STSA estimator Independent component analysis Blind source separation array signal processing islet cell antibody Mini Mental State Examination Speech SPECTRAL SUBTRACTION Noise artificial noise Computer Simulation

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