Vocal Tract Length Normalization

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Bias Adaptation for Vocal Tract Length Normalization

Vocal tract length normalisation (VTLN) is a well known rapid adaptation technique. VTLN as a linear transformation in the cepstral domain results in the scaling and translation factors. The warping factor represents the spectral scaling parameter. While, the translation factor represented by bias term captures more speaker characteristics especially in a rapid adaptation framework without havi...

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Dynamic Vocal Tract Length Normalization in Speech Recognition

A novel method to account for dynamic speaker characteristic properties in a speech recognition system is presented. The estimated trajectory of a property can be constrained to be constant or to have a limited rate-of-change within a phone or a sub-phone state. The constraints are implemented by extending each state in the trained Hidden Markov Model by a number of property-value-specific sub-...

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Applying vocal tract length normalization to meeting recordings

Vocal Tract Length Normalisation (VTLN) is a commonly used technique to normalise for inter-speaker variability. It is based on the speaker-specifi c warping of the frequency axis, parameterised by a scalar warp factor. This factor is typically estimated using maximum likelihood. We discuss how VTLN may be applied to multiparty conversations, reporting a substantial decrease in word error rate ...

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Vocal Tract Length Normalization for Large Vocabulary Continuous Speech Recognition

Generally speaking, the speaker-dependence of a speech recognition system stems from speaker-dependent speech feature. The variation of vocal tract length and/or shape is one of the major source of inter-speaker variations. In this paper, we address several methods of vocal tract length normalization (VTLN) for large vocabulary continuous speech recognition: (1) explore the bilinear warping VTL...

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Rapid vocal tract length normalization using maximum likelihood estimation

Recently, vocal tract length normalization (VTLN) techniques have been developed for speaker normalization in speech recognition. This paper proposes a new VTLN method, in which the vocal tract length is normalized in the cepstrum space by means of linear mapping whose parameter is derived using maximumlikelihood estimation. The computational costs of this method are much lower than that of suc...

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ژورنال

عنوان ژورنال: UC Berkeley Phonology Lab Annual Reports

سال: 2018

ISSN: 2768-5047

DOI: 10.5070/p7141042475