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Speech and Audio Processing, IEEE Transactions on

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Speech and Audio Processing, IEEE Transactions on

Issue 3 • Date Mar 2002

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Particle methods for Bayesian modeling and enhancement of speech signals

Time-domain parameterization of the closing phase of glottal airflow waveform from voices over a large intensity range

Robust endpoint detection and energy normalization for real-time speech and speaker recognition

A hierarchical language model based on variable-length class sequences: the MC_n^ν approach

Speaker verification in noise using a stochastic version of the weighted Viterbi algorithm

Substate tying with combined parameter training and reduction in tied-mixture HMM design

Extending the sound impulse response of room using extrapolation

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Speech and Audio Processing, IEEE Transactions on

Issue 3 • Date Mar 2002

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Title History

Particle methods for Bayesian modeling and enhancement of speech signals

Time-domain parameterization of the closing phase of glottal airflow waveform from voices over a large intensity range

Robust endpoint detection and energy normalization for real-time speech and speaker recognition

A hierarchical language model based on variable-length class sequences: the MCnν approach

Speaker verification in noise using a stochastic version of the weighted Viterbi algorithm

Substate tying with combined parameter training and reduction in tied-mixture HMM design

Extending the sound impulse response of room using extrapolation

Aims & Scope

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A hierarchical language model based on variable-length class sequences: the MC_n^ν approach