Investigation on inter speaker variability in the feature space
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Investigation on Inter-Speaker Variability in The Feature Space. Presenter : 陳彥達. Reference. R. Haeb-Umbach, “Investigation on Inter-Speaker Variability in The Feature Space”, ICASSP 99. Outline. Introduction A measure of inter-speaker variability Vocal tract normalization

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Investigation on Inter-Speaker Variability in The Feature Space

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Investigation on inter speaker variability in the feature space

Investigation on Inter-Speaker Variability in The Feature Space

Presenter : 陳彥達


Reference

Reference

  • R. Haeb-Umbach, “Investigation on Inter-Speaker Variability in The Feature Space”, ICASSP 99.


Outline

Outline

  • Introduction

  • A measure of inter-speaker variability

  • Vocal tract normalization

  • Cepstral mean and variance normalization


Introduction

Introduction

  • Adaptation

    • Reduce mismatch by adapting feature vectors or model parameters to the target environment.


Introduction 2

Introduction(2)

  • Normalization

    • Compute feature or model parameters that are insensitive to undesired variations of the speech signal.


Introduction 3

Introduction(3)

  • Fisher discriminant analysis

    • An early assessment of a feature set without running recognition first

    • The ratio of feature variability due to different phonemes and due to different speakers


A measure of inter speaker variability

A measure of inter-speaker variability

  • Good feature vector space

    • Close together when belonging to the same phoneme class

    • Separated from each other when belonging to the different phoneme class


A measure of inter speaker variability 2

A measure of inter-speaker variability(2)

: cepstral feature vectors

: cepstral mean feature vector

: class mean vector

: total mean vector


A measure of inter speaker variability 3

A measure of inter-speaker variability(3)

: cepstral mean feature vector

: class mean vector

: total mean vector

: between class covariance matrix

: within class covariance matrix


A measure of inter speaker variability 4

A measure of inter-speaker variability(4)

  • Fisher variate analysis

    • = the sum of the eigenvalues

      of

    • The radius of the scattering volume

    • Higher

      lower recognition error rate


Vocal tract normalization

Vocal tract normalization

  • Reduce inter-speaker variability by a speaker-specific frequency warping

  • Differences in vocal tract length are compensated for by a linear warping factor


Vocal tract normalization 2

Vocal tract normalization(2)

42 male + 42 female42 male


Vocal tract normalization 3

Vocal tract normalization(3)

a normalization on a per sentence basis performs better than a normalization on a per speaker basis


Cepstral mean and variance normalization

Cepstral mean and variance normalization

: input cepstral feature

: estimate of the mean of the input cepstral feature

: estimate of the standard deviation of the input cepstral feature

: the mean and variance normalized feature

: number of features


Cepstral mean and variance normalization 2

Cepstral mean and variance normalization(2)

42 male + 42 female 42 male


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