Concept

Phonotaxe

Publications associées (20)

Articulatory feature based continuous speech recognition using probabilistic lexical modeling

Phonological studies suggest that the typical subword units such as phones or phonemes used in automatic speech recognition systems can be decomposed into a set of features based on the articulators used to produce the sound. Most of the current approaches ...

Elsevier2016

Syllabic Pitch Tuning for Neutral-to-Emotional Voice Conversion

Milos Cernak, Lakshmi Babu Saheer

Prosody plays an important role in both identification and synthesis of emotionalized speech. Prosodic features like pitch are usually estimated and altered at a segmental level based on short windows of speech (where the signal is expected to be quasi-sta ...

Idiap2015

Joint Phoneme Segmentation Inference and Classification using CRFs

Ronan Collobert, Dimitri Palaz

State-of-the-art phoneme sequence recognition systems are based on hybrid hidden Markov model/artificial neural networks (HMM/ANN) framework. In this framework, the local classifier, ANN, is typically trained using Viterbi expectation-maximization algorith ...

2014

Articulatory Feature based Continuous Speech Recognition using Probabilistic Lexical Modeling

Ramya Rasipuram

Idiap2014

Syllable-based Pitch Encoding for Low Bit Rate Speech Coding with Recognition/Synthesis Architecture

Philip Neil Garner, Milos Cernak

Current HMM-based low bit rate speech coding systems work with phonetic vocoders. Pitch contour coding (on frame or phoneme level) is usually fairly orthogonal to other speech coding parameters. We make an assumption in our work that the speech signal cont ...

Idiap2013

Improving Grapheme-based ASR by Probabilistic Lexical Modeling Approach

Ramya Rasipuram

There is growing interest in using graphemes as subword units, especially in the context of the rapid development of hidden Markov model (HMM) based automatic speech recognition (ASR) system, as it eliminates the need to build a phoneme pronunciation lexic ...

Idiap2013

Improving Grapheme-based ASR by Probabilistic Lexical Modeling Approach

Ramya Rasipuram

2013

Probabilistic Lexical Modeling and Unsupervised Training for Zero-Resourced ASR

Ramya Rasipuram, Marzieh Razavi

Standard automatic speech recognition (ASR) systems rely on transcribed speech, language models, and pronunciation dictionaries to achieve state-of-the-art performance. The unavailability of these resources constrains the ASR technology to be available for ...

2013

Hierarchical Multilayer Perceptron based Language Identification

Hervé Bourlard, David Imseng

Automatic language identification (LID) systems generally exploit acoustic knowledge, possibly enriched by explicit language specific phonotactic or lexical constraints. This paper investigates a new LID approach based on hierarchical multilayer perceptron ...

Idiap2010

Hierarchical Multilayer Perceptron based Language Identification

Hervé Bourlard, David Imseng

2010

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