Inference in Switching Linear Dynamical Systems Applied to Noise Robust Speech Recognition of Isolated Digits
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State-of-the-art automatic speech recognition (ASR) techniques are typically based on hidden Markov models (HMMs) for the modeling of temporal sequences of feature vectors extracted from the speech signal. At the level of each HMM state, Gaussian mixture m ...
State-of-the-art automatic speech recognition (ASR) techniques are typically based on hidden Markov models (HMMs) for the modeling of temporal sequences of feature vectors extracted from the speech signal. At the level of each HMM state, Gaussian mixture m ...
An approach to analysis of time series of edge localized modes (ELMs) is proposed. It is based on the use of the autoregressive moving average model, which decomposes time series into deterministic and noise components. Despite the inclusion of nonlinearit ...
State-of-the-art automatic speech recognition (ASR) techniques are typically based on hidden Markov models (HMMs) for the modeling of temporal sequences of feature vectors extracted from the speech signal. At the level of each HMM state, Gaussian mixture m ...
Most conventional features used in speaker authentication are based on estimation of spectral envelopes in one way or another, in the form of cepstrums, e.g., Mel-scale Filterbank Cepstrum Coefficients (MFCCs), Linear-scale Filterbank Cepstrum Coefficients ...
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Recently, a nonlinear transformation of autocorrelation coefficients named Phase AutoCorrelation (PAC) coefficients has been considered for feature extraction \cite{ikbal03}. PAC based features show improved robustness to additive noise as a result of two ...
This article introduces a novel technique for estimating the signal power spectral density to be used in the transfer function of a microphone array post-filter. The technique is a generalisation of the existing Zelinski post-filter, which uses the auto- a ...
Recently, a nonlinear transformation of autocorrelation coefficients named Phase AutoCorrelation (PAC) coefficients has been considered for feature extraction \cite{ikbal03}. PAC based features show improved robustness to additive noise as a result of two ...
