Articulatory feature-based pronunciation modeling

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Articulatory feature-based pronunciation modeling

Spoken language, especially conversational speech, is characterized by great variability in word pronunciation, including many variants that differ grossly from dictionary prototypes. This is one factor in the poor performance of automatic speech recognizers on conversational speech, and it has been very difficult to mitigate in traditional phonebased approaches to speech recognition. An altern...

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Adaptive articulatory feature-based conditional pronunciation modeling for speaker verification

Because of the differences in education background, accents, and so on, different persons have different ways of pronunciation. Therefore, the pronunciation patterns of individuals can be used as features for discriminating speakers. This paper exploits the pronunciation characteristics of speakers and proposes a new conditional pronunciation modeling (CPM) technique for speaker verification. T...

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Articulatory feature-based conditional pronunciation modeling for speaker verification

Because of the differences in education background, accents, etc., different persons have their unique way of pronunciation. This paper exploits the pronunciation characteristics of speakers and proposes a new conditional pronunciation modeling (CPM) technique for speaker verification. The proposed technique aims to establish a link between articulatory properties (e.g., manners and places of a...

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Modeling pronunciation variation with context-dependent articulatory feature decision trees

We consider the problem of predicting the surface pronunciations of a word in conversational speech, using a model of pronunciation variation based on articulatory features. We build context-dependent decision trees for both phone-based and feature-based models, and compare their perplexities on conversational data from the Switchboard Transcription Project. We find that a fully-factored model,...

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High-level feature-based speaker verification via articulatory phonetic-class pronunciation modeling

Although articulatory feature-based conditional pronunciation models (AFCPMs) can capture the pronunciation characteristics of speakers, they requires one discrete density function for each phoneme, which may lead to inaccurate models when the amount of training data is limited. This paper proposes a phonetic-class based AFCPM in which the density functions in speaker models are conditioned on ...

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ژورنال

عنوان ژورنال: Computer Speech & Language

سال: 2016

ISSN: 0885-2308

DOI: 10.1016/j.csl.2015.07.003