Acoustic Data-driven Grapheme-to-Phoneme Conversion using KL-HMM
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This paper proposes a novel grapheme-to-phoneme (G2P) conversion approach where first the probabilistic relation between graphemes and phonemes is captured from acoustic data using Kullback-Leibler divergence based hidden Markov model (KL-HMM) system. Then ...
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 ...
In a recent work, we proposed an acoustic data-driven grapheme-to-phoneme (G2P) conversion approach, where the probabilistic relationship between graphemes and phonemes learned through acoustic data is used along with the orthographic transcription of word ...
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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 ...
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 ...
The state-of-the-art automatic speech recognition (ASR) systems typically use phonemes as subword units. In this work, we present a novel grapheme-based ASR system that jointly models phoneme and grapheme information using Kullback-Leibler divergence-based ...
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 ...
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 ...
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 ...
