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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 ...
École Polytechnique Fédérale de Lausanne, Computer Science Department2005
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 ...
Nd-Nickelate (NNO), Nd1.95NiO4+delta, an alternative solid oxide fuel cell cathode material, has been imaged and mapped in 3D using synchrotron-based x-ray nanotomography. The NNO cathode material, which suffered from silicon contamination during fabricati ...
Security protocols are essential to the proper functioning of any distributed system running over an insecure network but often have flaws that can be exploited even without breaking the cryptography. Formal cryptography, the assumption that the cryptograp ...
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 ...
In this paper we present a study of automatic speech recognition systems using context-dependent phonemes and graphemes as sub-word units based on the conventional HMM/GMM system as well as tandem system. Experimental studies conducted on three different c ...
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 ...
State-of-the-art Automatic Speech Recognition (ASR) systems typically use phoneme as the subword units. In this paper, we investigate a system where the word models are defined in-terms of two different subword units, i.e., phonemes and graphemes. We train ...
State-of-the-art Automatic Speech Recognition (ASR) systems typically use phoneme as the subword units. In this paper, we investigate a system where the word models are defined in-terms of two different subword units, i.e., phonemes and graphemes. We train ...
