Journal ArticleDOI
Enhancement of reverberant speech using LP residual signal
B. Yegnanarayana,P.S. Murthy +1 more
TLDR
A new method of processing speech degraded by reverberation based on analysis of short segments of data to enhance the regions in the speech signal having a high signal-to-reverberant component ratio (SRR).Abstract:
We propose a new method of processing speech degraded by reverberation. The method is based on analysis of short (2 ms) segments of data to enhance the regions in the speech signal having a high signal-to-reverberant component ratio (SRR). The short segment analysis shows that SRR is different in different segments of speech. The processing method involves identifying and manipulating the linear prediction residual signal in three different regions of the speech signal, namely, high SRR region, low SRR region, and only reverberation component region. A weight function is derived to modify the linear prediction residual signal. The weighted residual signal samples are used to excite a time-varying all-pole filter to obtain perceptually enhanced speech. The method is robust to noise present in the recorded speech signal. The performance is illustrated through spectrograms, subjective and objective evaluations.read more
Citations
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Journal ArticleDOI
Epoch Extraction From Speech Signals
K.S.R. Murty,B. Yegnanarayana +1 more
TL;DR: The interesting part of the results is that the epoch extraction by the proposed method seems to be robust against degradations like white noise, babble, high-frequency channel, and vehicle noise.
Book
Speech Dereverberation
TL;DR: Speech Dereverberation presents the most important current approaches to the problem of reverberation and defines the current state of the art and encourages further work on this topic by offering open research questions to exercise the curiosity of the reader.
Journal ArticleDOI
Detection of Glottal Closure Instants From Speech Signals: A Quantitative Review
TL;DR: In this paper, five state-of-the-art GCI detection algorithms are compared using six different databases with contemporaneous electroglottographic recordings as ground truth, and containing many hours of speech by multiple speakers.
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.
Journal ArticleDOI
A two-stage algorithm for one-microphone reverberant speech enhancement
Mingyang Wu,DeLiang Wang +1 more
TL;DR: A comparison with a recent enhancement algorithm is made on a corpus of speech utterances in a number of reverberant conditions, and the results show that the proposed algorithm performs substantially better.
References
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Numerical recipes in C
TL;DR: The Diskette v 2.06, 3.5''[1.44M] for IBM PC, PS/2 and compatibles [DOS] Reference Record created on 2004-09-07, modified on 2016-08-08.
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TL;DR: This chapter discusses the concept of a Random Variable, the meaning of Probability, and the axioms of probability in terms of Markov Chains and Queueing Theory.
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Suppression of acoustic noise in speech using spectral subtraction
TL;DR: A stand-alone noise suppression algorithm that resynthesizes a speech waveform and can be used as a pre-processor to narrow-band voice communications systems, speech recognition systems, or speaker authentication systems.
Book
Discrete-Time Processing of Speech Signals
TL;DR: The preface to the IEEE Edition explains the background to speech production, coding, and quality assessment and introduces the Hidden Markov Model, the Artificial Neural Network, and Speech Enhancement.