Proceedings ArticleDOI
On the use of explicit speech modeling in microphone array applications
M.S. Brandstein
- Vol. 6, pp 3613-3616
TLDR
This paper addresses the limitations of current approaches to distant-talker speech acquisition and advocates the development of techniques which explicitly incorporate the nature of the speech signal into a multi-channel context.Abstract:
This paper addresses the limitations of current approaches to distant-talker speech acquisition and advocates the development of techniques which explicitly incorporate the nature of the speech signal (e.g. statistical non-stationarity, method of production, pitch, voicing, formant structure, and source radiator model) into a multi-channel context. The goal is to combine the advantages of spatial filtering achieved through beamforming with knowledge of the desired time-series attributes. The potential utility of such an approach is demonstrated through the application of a multi-channel version of the dual excitation speech model.read more
Citations
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Single- and multi-microphone speech dereverberation using spectral enhancement
TL;DR: Novel single- and multimicrophone speech dereverberation algorithms are developed that aim at the suppression of late reverberation, i.e., signal processing techniques to reduce the detrimental effects of reflections.
Proceedings ArticleDOI
Speech dereverberation via maximum-kurtosis subband adaptive filtering
TL;DR: An efficient algorithm for high-quality speech capture in applications such as hands-free teleconferencing or voice recording by personal computers using a modulated complex lapped transform (MCLT), in which the subband filters are adapted to maximize the kurtosis of the linear prediction residual of the reconstructed speech.
PatentDOI
Method and apparatus for removing noise from feature vectors
TL;DR: In this paper, a method and computer-readable medium are provided for identifying clean signal feature vectors from noisy signal feature vector, which is based on variational inference techniques, using an iterative approach to identify the clean signal vector.
Proceedings Article
Speech Denoising and Dereverberation Using Probabilistic Models
TL;DR: A unified probabilistic framework for denoising and dereverberation of speech signals that is to use a strong speech model that is pre-trained on a large data set of clean speech to get results substantially better than standard methods.
Journal ArticleDOI
A Supervised Learning Approach to Monaural Segregation of Reverberant Speech
Zhaozhang Jin,DeLiang Wang +1 more
TL;DR: A supervised learning approach to monaural segregation of reverberant voiced speech is proposed, which learns to map from a set of pitch-based auditory features to a grouping cue encoding the posterior probability of a time-frequency (T-F) unit being target dominant given observed features.
References
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Don H. Johnson,Dan E. Dudgeon +1 more
TL;DR: This chapter discusses how signals in Space and Time and apertures and Arrays affect Array Processing and the role that symbols play in this processing.
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Speech analysis/Synthesis based on a sinusoidal representation
R.J. McAulay,Thomas F. Quatieri +1 more
TL;DR: A sinusoidal model for the speech waveform is used to develop a new analysis/synthesis technique that is characterized by the amplitudes, frequencies, and phases of the component sine waves, which forms the basis for new approaches to the problems of speech transformations including time-scale and pitch-scale modification, and midrate speech coding.
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TL;DR: The author explains the development of the Wiener Solution and some of the techniques used in its implementation, including Optimum Processing: Steady State Performance and theWiener Solution, which simplifies the implementation of the Covariance Matrix.