Acoustic data-driven grapheme-to-phoneme conversion in the probabilistic lexical modeling framework
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Standard hidden Markov model (HMM) based automatic speech recognition (ASR) systems usually use cepstral features as acoustic observation and phonemes as subword units. Speech signal exhibits wide range of variability such as, due to environmental variatio ...
Standard hidden Markov model (HMM) based automatic speech recognition (ASR) systems usually use cepstral features as acoustic observation and phonemes as subword units. Speech signal exhibits wide range of variability such as, due to environmental variatio ...
École Polytechnique Fédérale de Lausanne, Computer Science Department2005
Standard hidden Markov model (HMM) based automatic speech recognition (ASR) systems usually use cepstral features as acoustic observation and phonemes as subword units. Speech signal exhibits wide range of variability such as, due to environmental variatio ...
EPFL2005
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This paper investigates automatic speech recognition system using context-dependent graphemes as subword units based on the conventional HMM/GMM system as well as TANDEM system. Experimental studies conducted on two different continuous speech recognition ...
IDIAP2005
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In this report, we propose a discriminative decoder for phoneme recognition, i.e. the identification of the uttered phoneme sequence from a speech recording. This task is solved as a 3 step process: a phoneme classifier first classifies each accoustic fram ...
IDIAP2005
The paper presents a new approach to spotting a particular sound (keyword) in an acoustic stream. The approach is based on hierarchical processing where equally-sampled posterior probabilities of phoneme classes are estimated first, followed by matched fil ...
In this paper, we analyze the confusions patterns at three places in the hybrid phoneme recognition system. The confusions are analyzed at the pronunciation, the posterior probability, and the phoneme recognizer levels. The confusions show significant stru ...
In recent literature, different approaches have been proposed to use graphemes as subword units with implicit source of phoneme information for automatic speech recognition. The major advantage of using graphemes as subword units is that the definition of ...
Standard ASR systems typically use phoneme as the subword units. Preliminary studies have shown that the performance of the ASR system could be improved by using grapheme as additional subword units. In this paper, we investigate such a system where the wo ...
IDIAP2003
,
Standard ASR systems typically use phoneme as the subword units. Preliminary studies have shown that the performance of the ASR system could be improved by using grapheme as additional subword units. In this paper, we investigate such a system where the wo ...
