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Using Auxiliary Sources of Knowledge for Automatic Speech Recognition

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A Comparison of Supervised and Unsupervised Cross-Lingual Speaker Adaptation Approaches for HMM-Based Speech Synthesis

John David Scott Dines, Hui Liang, Lakshmi Babu Saheer

The EMIME project aims to build a personalized speech-to-speech translator, such that spoken input of a user in one language is used to produce spoken output that still sounds like the user's voice however in another language. This distinctiveness makes un ...

2010

Overcoming Asynchrony in Audio-Visual Speech Recognition

Jean-Philippe Thiran, Virginia Estellers Casas

In this paper we propose two alternatives to overcome the natural asynchrony of modalities in Audio-Visual Speech Recognition. We first investigate the use of asynchronous statistical models based on Dynamic Bayesian Networks with different levels of async ...

2010

Towards mixed language speech recognition systems

Hervé Bourlard, David Imseng

Multilingual speech recognition obviously involves numerous research challenges, including common phoneme sets, adaptation on limited amount of training data, as well as mixed language recognition (common in many countries, like Switzerland). In this latte ...

2010

Towards mixed language speech recognition systems

Hervé Bourlard, David Imseng

Idiap2010

A Kernel Wrapper for Phoneme Sequence Recognition

We describe a kernel wrapper, a Mercer kernel for the task of phoneme sequence recognition which is based on operations with the Gaussian kernel, and suitable for any sequence kernel classifier. We start by presenting a kernel-based algorithm for phoneme s ...

John Wiley and Sons2009

On Joint Modelling of Grapheme and Phoneme Information using KL-HMM for ASR

Hervé Bourlard, Guillermo Aradilla

In this paper, we propose a simple approach to jointly model both grapheme and phoneme information using Kullback-Leibler divergence based HMM (KL-HMM) system. More specifically, graphemes are used as subword units and phoneme posterior probabilities estim ...

Idiap2009

Discriminative Keyword Spotting

Samy Bengio, David Grangier

This chapter introduces a discriminative method for detecting and spotting keywords in spoken utterances. Given a word represented as a sequence of phonemes and a spoken utterance, the keyword spotter predicts the best time span of the phoneme sequence in ...

John Wiley and Sons2009

Enhancing posterior based speech recognition systems

Hamed Ketabdar

The use of local phoneme posterior probabilities has been increasingly explored for improving speech recognition systems. Hybrid hidden Markov model / artificial neural network (HMM/ANN) and Tandem are the most successful examples of such systems. In this ...

EPFL2008

Enhancing posterior based speech recognition systems

Hamed Ketabdar

Ecole Polytechnique Fédérale de Lausanne2008

Fast Approximate Spoken Term Detection from Sequence of Phonemes

Hynek Hermansky, Joel Praveen Pinto

We investigate the detection of spoken terms in conversational speech using phoneme recognition with the objective of achieving smaller index size as well as faster search speed. Speech is processed and indexed as a sequence of one best phoneme sequence. W ...

2008