In this paper, we propose a method for decomposing speech signals, evaluating the discriminative, and determining the representative vectors of signal sets.
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Abstract— In this paper, we propose a method for decomposing speech signals, evaluating the discriminative, and determining the representative vectors of ...
In this paper, we propose a method for decomposing speech signals, evaluating the discriminative, and determining the representative vectors of signal sets.
on the frequency domain analysis of speech signals. In this paper the author presents a new technique using wavelet transforms and zero crossing counting to ...
Missing: Discriminative | Show results with:Discriminative
In this work, we investigate the use of discriminative models for automatic speech recognition of subvocalic speech via surface electromyography (sEMG).
Bibliographic details on Discriminative of wavelet sub-signals for speech recognition.
In this paper, a new feature extraction methodology based on. Wavelet Transforms is examined, which unlike some conventional parameterisation techniques ...
Missing: Discriminative | Show results with:Discriminative
Wavelets have been shown to be useful front end processors for speech recognition systems for discriminative tasks. These speech recognition systems have been ...
This paper addresses the problem of parameterization for speech/music discrimination. The current successful parameterization based on cepstral coefficients ...
Missing: Discriminative | Show results with:Discriminative
People also ask
What kind of signal is used in speech recognition?
What are the spectral features for speech recognition?
A feature extraction methodology based on wavelet transforms is examined in the paper "Discriminant wavelet basis construction for speech recognition" by Long ...