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Interspeech Conference

作者： Wang, Dongmei Chen, Zhuo Yoshioka, Takuya Microsoft One Microsoft Way Redmond WA 98052 USA

ISBN: (纸本)9781713820697

This paper proposes a neural network based speech separation method using spatially distributed microphones. Unlike with traditional microphone array settings, neither the number of microphones nor their spatial arrangement is known in advance, which hinders the use of conventional multi-channel speech separation neural networks based on fixed size input. To overcome this, a novel network architecture is proposed that interleaves inter-channel processing layers and temporal processing layers. The inter-channel processing layers apply a self-attention mechanism along the channel dimension to exploit the information obtained with a varying number of microphones. The temporal processing layers are based on a bidirectional long short term memory (BLSTM) model and applied to each channel independently. The proposed network leverages information across time and space by stacking these two kinds of layers alternately. Our network estimates time-frequency (TF) masks for each speaker, which are then used to generate enhanced speech signals either with TF masking or beamforming. Speech recognition experimental results show that the proposed method significantly outperforms baseline multi-channel speech separation systems.

关键词： distributed microphone array ad hoc array speech separation overlapped speech distant speech recognition

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The INTERSPEECH 2020 Far-Field Speaker Verification Challenge 21

The INTERSPEECH 2020 Far-Field Speaker Verification Challeng...

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Interspeech Conference

作者： Qin, Xiaoyi Li, Ming Bu, Hui Rao, Wei Das, Rohan Kumar Narayanan, Shrikanth Li, Haizhou Duke Kunshan Univ Data Sci Res Ctr Kunshan Peoples R China Natl Univ Singapore Dept Elect & Comp Engn Singapore Singapore Univ Southern Calif Signal Anal & Interpretat Lab Los Angeles CA 90007 USA AI Shell Fdn Beijing Peoples R China Wuhan Univ Sch Comp Sci Wuhan Peoples R China

ISBN: (纸本)9781713820697

The INTERSPEECH 2020 Far-Field Speaker Verification Challenge (FFSVC 2020) addresses three different research problems under well-defined conditions: far-field text-dependent speaker verification from single microphone array, far-field text-independent speaker verification from single microphone array, and far-field text-dependent speaker verification from distributed microphone arrays. All three tasks pose a cross-channel challenge to the participants. To simulate the real-life scenario, the enrollment utterances are recorded from close-talk cellphone, while the test utterances are recorded from the far-field microphone arrays. In this paper, we describe the database, the challenge, and the baseline system, which is based on a ResNet-based deep speaker network with cosine similarity scoring. For a given utterance, the speaker embeddings of different channels are equally averaged as the final embedding. The baseline system achieves minDCFs of 0.62, 0.66, and 0.64 and EERs of 6.27%, 6.55%, and 7.18% for task 1, task 2, and task 3, respectively.

关键词： Speaker verification Far-field Cross channel matching distributed microphone array Enrollment augmentation

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Direction of Arrival Estimation Using distributed Circular microphone arrays 14

Direction of Arrival Estimation Using Distributed Circular M...

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14th IEEE International Conference on Signal Processing (ICSP)

作者： Chen, Tingwei Huang, Qinghua Zhang, Lili Fang, Yong Shanghai Univ Key Lab Specialty Fiber Opt & Opt Access NetWorks Shanghai Peoples R China

ISBN: (纸本)9781538646731

This paper considers a new method for estimating Direction of Arrival (DOA) of plane waves using distributed circular microphone arrays. Sound field produced by incident waves is decomposed into circular harmonics functions, and then we can obtain an expression of the circular harmonics coefficients. The expression is associated with position in the sound field. This formulation enables us to obtain a virtual uniform circular array from the distributed microphone array. Then we use Estimating Signal Parameter via Rotational techniques (ESPRIT) to estimate the source DOA based on a recursive relationship of Bessel functions. Simulations demonstrate that the proposed method can get higher accuracy than conventional method for distributed microphone array.

关键词： DOA estimation distributed microphone array Estimating Signal Parameter via Rotational techniques (ESPRIT) sound field decomposition

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Blind Synchronization in Wireless Acoustic Sensor Networks

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IEEE-ACM TRANSACTIONS ON AUDIO SPEECH AND LANGUAGE PROCESSING 2017年第3期25卷 651-661页

作者： Cherkassky, Dani Gannot, Sharon Bar Ilan Univ Fac Engn IL-52900 Ramat Gan Israel

The challenge of blindly resynchronizing the data ac-quisition processes in a wireless acoustic sensor network (WASN) is addressed in this paper. The sampling rate offset (SRO) is precisely modeled as a time scaling. The applicability of a wideband corre-lation processor for estimating the SRO, even in a reverberant and multiple source environment, is presented. An explicit expression for the ambiguity function, which in our case involves time scaling of the received signals, is derived by applying truncated band-limited interpolation. We then propose the recursive band-limited interpolation (RBI) algorithm for recursive SRO estimation. A complete resynchronization scheme utilizing the RBI algorithm, in parallel with the SRO compensation module, is presented. The resulting resynchronizationmethod operates in the time domain in a sequential manner and is, thus, capable of tracking a potentially time-varying SRO. We compared the performance of the proposed RBI algorithm to other available methods in a simulation study. The importance of resynchronization in a beamforming applica-tion is demonstrated by both a simulation study and experiments with a realWASN. Finally, we present an experimental study eval-uating the expected SRO level between typical data acquisition devices.

关键词： Blind synchronization distributed microphone array sampling rate offset wireless acoustic sensor network wide-band correlation processing

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Sound Source and microphone Localization From Acoustic Impulse Responses

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IEEE SIGNAL PROCESSING LETTERS 2016年第10期23卷 1459-1463页

作者： Salvati, Daniele Drioli, Carlo Foresti, Gian Luca Univ Udine Dept Math Comp Sci & Phys I-33100 Udine Italy

This letter proposes a new method for source and microphone localization in reverberant environments using a randomly arranged sensor array, under the hypothesis that the position of one reference sensor and the geometry of the environment are known, and the other microphone positions are unknown. A minimum mean square error (MMSE) estimator that exploits early reflections is proposed. The MMSE estimator is solved by a grid search method that combines the information on early reflections estimated using a multichannel blind system identification and the time difference of arrivals between the reflections and the direct-path calculated with the image-source model. Simulations under different reverberant scenarios demonstrate the ability of the proposed approaches in localizing source and microphone.

关键词： distributed microphone array image-microphone model microphone position calibration multichannel blind system identification (BSI) sound source localization

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WIENER FILTER DESIGN BY ESTIMATING SENSITIVITIES BETWEEN distributed ASYNCHRONOUS microphoneS AND SOUND SOURCES

WIENER FILTER DESIGN BY ESTIMATING SENSITIVITIES BETWEEN DIS...

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IEEE Workshop on Applications of Signal Processing to Audio and Acoustics (WASPAA)

作者： Kako, Tatsuya Niwa, Kenta Kobayashi, Kazunori Ohmuro, Hitoshi NTT Media Intelligence Labs 3-9-11 Midori Cho Musashino Shi Tokyo 1808585 Japan

ISBN: (纸本)9781479974504

A Wiener filter design method for distributed asynchronous microphones is proposed. The major approach to speech enhancement with a distributed microphone array has been to form directivity after adjusting the sampling rate between asynchronous microphones. However, since the synchronization accuracy varies with the source signal, noise reduction performance is often degraded. To achieve speech enhancement without accurate synchronization adjustment, we applied Wiener filtering to the highest signal-to-noise ratio (SNR) microphone observation signal. To design a Wiener filter, which is composed of the estimated power spectrum density (PSD) of a target source and other noises, it is necessary to estimate the sensitivities between sound sources and microphones and the number of sound sources without prior information. Under the assumption that source signals are sparse in the time-frequency domain, the sensitivities from a sound source to the microphones are estimated from observed signals. By classifying the estimated sensitivities, the number of sound sources is estimated. Through experiments with asynchronous microphones implemented in smart-phones, we confirmed that the sensitivities between sound sources and microphones were estimated accurately and that the output SNR was improved with the proposed method.

关键词： distributed microphone array speech enhancement Wiener filter power spectrum density (PSD)

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Pseudo-coherence-based MVDR beamformer for speech enhancement with ad hoc microphone arrays 40

Pseudo-coherence-based MVDR beamformer for speech enhancemen...

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40th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2015

作者： Tavakoliy, Vincent Mohammad Jenseny, Jesper Rindom Christenseny, Mads Graesboll Benestyz, Jacob Audio Analysis Lab AD:MT Aalborg University Denmark INRS-EMT University of Quebec Montreal Canada

ISBN: (纸本)9781467369978

Speech enhancement with distributed arrays has been met with various methods. On the one hand, data independent methods require information about the position of sensors, so they are not suitable for dynamic geometries. On the other hand, Wiener-based methods cannot assure a distortionless output. This paper proposes minimum variance distortionless response filtering based on multichannel pseudo-coherence for speech enhancement with ad hoc microphone arrays. This method requires neither position information nor control of the trade-off used in the distortion weighted methods. Furthermore, certain performance criteria are derived in terms of the pseudo-coherence vector, and the method is compared with the multichannel Wiener filter. Evaluation shows the suitability of the proposed method in terms of noise reduction with minimum distortion in ad hoc scenarios. © 2015 IEEE.

关键词： distributed microphone array MVDR filter Noise reduction speech enhancement STFT domain

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MULTICHANNEL FEATURE ENHANCEMENT IN distributed microphone arrayS FOR ROBUST DISTANT SPEECH RECOGNITION IN SMART ROOMS

MULTICHANNEL FEATURE ENHANCEMENT IN DISTRIBUTED MICROPHONE A...

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IEEE Workshop on Spoken Language Technology (SLT 2014)

作者： Mirsamadi, Seyedmahdad Hansen, John H. L. Univ Texas Dallas CRSS Richardson TX 75080 USA

ISBN: (纸本)9781479971299

Room reverberation and environmental noise present challenges for integration of speech recognition technology in smart room applications. We present a multichannel enhancement framework for distributed microphone arrays to mitigate the effects of both additive noise and reverberation on distant-talking microphones. The proposed approach uses techniques of nonnegative matrix and tensor factorization to achieve both noise suppression (through sparse representation of speech spectra) and dereverberation (through decomposition of magnitude spectra into convolutive components). Results of ASR experiments on the DIRHA-GRID corpus confirm that the proposed approach can achieve relative improvements of up to +20% in recognition accuracy in highly reverberant and noisy conditions using clean-trained models.

关键词： distant speech recognition distributed microphone array nonnegative matrix/tensor factorization

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WIENER FILTER DESIGN BY ESTIMATING SENSITIVITIES BETWEEN distributed ASYNCHRONOUS microphoneS AND SOUND SOURCES

WIENER FILTER DESIGN BY ESTIMATING SENSITIVITIES BETWEEN DIS...

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IEEE Workshop on Applications of Signal Processing to Audio and Acoustics

作者： Tatsuya Kako Kenta Niwa Kazunori Kobayashi Hitoshi Ohmuro NTT Media Intelligence Laboratories

ISBN: (纸本)9781479974511

A Wiener filter design method for distributed asynchronous microphones is proposed. The major approach to speech enhancement with a distributed microphone array has been to form directivity after adjusting the sampling rate between asynchronous microphones. However, since the synchronization accuracy varies with the source signal, noise reduction performance is often degraded. To achieve speech enhancement without accurate synchronization adjustment, we applied Wiener filtering to the highest signal-to-noise ratio (SNR) microphone observation signal. To design a Wiener filter, which is composed of the estimated power spectrum density (PSD) of a target source and other noises, it is necessary to estimate the sensitivities between sound sources and microphones and the number of sound sources without prior information. Under the assumption that source signals are sparse in the time-frequency domain, the sensitivities from a sound source to the microphones are estimated from observed signals. By classifying the estimated sensitivities, the number of sound sources is estimated. Through experiments with asynchronous microphones implemented in smartphones, we confirmed that the sensitivities between sound sources and microphones were estimated accurately and that the output SNR was improved with the proposed method.

关键词： distributed microphone array Speech enhancement Wiener filter Power spectrum density (PSD)

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Pseudo-coherence-based MVDR beamformer for speech enhancement with ad hoc microphone arrays

Pseudo-coherence-based MVDR beamformer for speech enhancemen...

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IEEE International Conference on Acoustics, Speech and Signal Processing

作者： V. M. Tavakoli J. R. Jensen M. G. Christenseny J. Benesty Audio Anal. Lab. Aalborg Univ. Aalborg Denmark

ISBN: (纸本)9781467369985

关键词： MVDR filter Noise reduction STFT domain distributed microphone array speech enhancement Speech enhancement Noise reduction ad hoc distortionless microphone arrays

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