Publications associées à Automatic pathological speech assessment

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Source/Filter Factorial Hidden Markov Model, with Application to Pitch and Formant Tracking

Jean-Philippe Thiran

Tracking vocal tract formant frequencies (

f_p

) and estimating the fundamental frequency (

f_0

) are two tracking problems that have been tackled in many speech processing works, often independently, with applications to articulatory parameters estimation ...

Institute of Electrical and Electronics Engineers2013

Automatic pathological speech assessment

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Estimating Phoneme Class Conditional Probabilities from Raw Speech Signal using Convolutional Neural Networks

Model-based Sparse Component Analysis for Multiparty Distant Speech Recognition

Joint Source-Filter Optimization for Accurate Vocal Tract Estimation Using Differential Evolution

Crosslingual Tandem-SGMM: Exploiting Out-Of-Language Data for Acoustic Model and Feature Level Adaptation

Crosslingual Tandem-SGMM: Exploiting Out-Of-Language Data for Acoustic Model and Feature Level Adaptation

Source/Filter Factorial Hidden Markov Model, with Application to Pitch and Formant Tracking

Who Wants To Be A Millionaire? (II)

Multi-parametric source-filter separation of speech and prosodic voice restoration

Data-Driven Enhancement of State Mapping-Based Cross-Lingual Speaker Adaptation

Speaker diarization of overlapping speech based on silence distribution in meeting recordings

Data-Driven Enhancement of State Mapping-Based Cross-Lingual Speaker Adaptation

Estimating Phoneme Class Conditional Probabilities from Raw Speech Signal using Convolutional Neural Networks

Multi-parametric source-filter separation of speech and prosodic voice restoration

Speaker diarization of overlapping speech based on silence distribution in meeting recordings

Who Wants To Be A Millionaire? (II)

Joint Source-Filter Optimization for Accurate Vocal Tract Estimation Using Differential Evolution

Model-based Sparse Component Analysis for Multiparty Distant Speech Recognition

Source/Filter Factorial Hidden Markov Model, with Application to Pitch and Formant Tracking

Crosslingual Tandem-SGMM: Exploiting Out-Of-Language Data for Acoustic Model and Feature Level Adaptation

Crosslingual Tandem-SGMM: Exploiting Out-Of-Language Data for Acoustic Model and Feature Level Adaptation