Speech Processing & Text-Independent Automatic Person Verification
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The speech signal conveys information on different time scales from short (20--40 ms) time scale or segmental, associated to phonological and phonetic information to long (150--250 ms) time scale or supra segmental, associated to syllabic and prosodic info ...
The speech signal conveys information on different time scales from short (20--40 ms) time scale or segmental, associated to phonological and phonetic information to long (150--250 ms) time scale or supra segmental, associated to syllabic and prosodic info ...
The speech signal conveys information on different time scales from short (20–40 ms) time scale or segmental, associated to phonological and phonetic information to long (150–250 ms) time scale or supra segmental, associated to syllabic and prosodic inform ...
The continuous increase, witnessed in the last decade, of both the amount of available data and the areas of application of machine learning, has lead to a demand for both learning and planning algorithms that are capable of handling large-scale problems. ...
In hybrid hidden Markov model/artificial neural networks (HMM/ANN) automatic speech recognition (ASR) system, the phoneme class conditional probabilities are estimated by first extracting acoustic features from the speech signal based on prior knowledge su ...
In hybrid hidden Markov model/artificial neural networks (HMM/ANN) automatic speech recognition (ASR) system, the phoneme class conditional probabilities are estimated by first extracting acoustic features from the speech signal based on prior knowledge su ...
This research takes place in the general context of improving the performance of the Distant Speech Recognition (DSR) systems, tackling the reverberation and recognition of overlap speech. Perceptual modeling indicates that sparse representation exists in ...
In this thesis, we propose a novel approach for speaker and speech recognition involving localized, binary, data-driven features. The proposed approach is largely inspired by similar localized approaches in the computer vision domain. The success of these ...
In this thesis, we propose a novel approach for speaker and speech recognition involving localized, binary, data-driven features. The proposed approach is largely inspired by similar localized approaches in the computer vision domain. The success of these ...
Ecole Polytechnique Federale de Lausanne (EPFL)2011
Progressive apraxia of Speech (PAoS) is a progressive motor speech disorder associated with neurodegenerative disease causing impairment of phonetic encoding and motor speech planning. Clinical observation and acoustic studies show that duration analysis p ...
