Proceedings ArticleDOI
A microphone array with adaptive post-filtering for noise reduction in reverberant rooms
R. Zelinski
- Vol. 5, pp 2578-2581
TLDR
The author presents a self-adapting noise reduction system which is based on a four-microphone array combined with an adaptive postfiltering scheme which produces an enhanced speech signal with barely noticeable residual noise if the input SNR is greater than 0 dB.Abstract:
The author presents a self-adapting noise reduction system which is based on a four-microphone array combined with an adaptive postfiltering scheme. Noise reduction is achieved by utilizing the directivity gain of the array and by reducing the residual noise through postfiltering of the received microphone signals. The postfiltering scheme depends on a Wiener filter estimating the desired speech signal and is computed from short-term measurements of the autocorrelation and cross-correlation functions of the microphone signals. The noise reduction system has been tested experimentally in a typical office room. The system produces an enhanced speech signal with barely noticeable residual noise if the input SNR is greater than 0 dB. The received noise power-measured in the absence of the speech signal-can be reduced by 28 dB. >read more
Citations
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Journal ArticleDOI
Signal enhancement using beamforming and nonstationarity with applications to speech
TL;DR: This paper considers a sensor array located in an enclosure, where arbitrary transfer functions (TFs) relate the source signal and the sensors, and derives a suboptimal algorithm that can be implemented by estimating theTFs ratios, instead of estimating the TFs.
BookDOI
Acoustical and environmental robustness in automatic speech recognition
TL;DR: This dissertation describes a number of algorithms developed to increase the robustness of automatic speech recognition systems with respect to changes in the environment, including the SNR-Dependent Cepstral Normalization, (SDCN) and the Codeword-Dependent Cep stral normalization (CDCN).
Journal ArticleDOI
A Consolidated Perspective on Multimicrophone Speech Enhancement and Source Separation
TL;DR: This paper proposes to analyze a large number of established and recent techniques according to four transverse axes: 1) the acoustic impulse response model, 2) the spatial filter design criterion, 3) the parameter estimation algorithm, and 4) optional postfiltering.
A High-Accuracy, Low-Latency Technique for Talker Localization in Reverberant Environments Using Microphone Arrays
TL;DR: He went on to Brown University in Providence, Rhode Island to study signal processing and began research on microphone arrays and received a Master of Science degree in Electrical Engineering in 1993 and continued to pursue his work towards a Doctor of Philosophy degree.
Journal ArticleDOI
An analysis of environment, microphone and data simulation mismatches in robust speech recognition
TL;DR: It is found that training on different noise environments and different microphones barely affects the ASR performance, especially when several environments are present in the training data: only the number of microphones has a significant impact.
References
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