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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 ...
In hybrid hidden Markov model/artificial neural networks (HMM/ANN) automatic speech recognition (ASR) system, the phoneme class conditional probabilities are estimated by first extracting acoustic features from the speech signal based on prior knowledge su ...
One of the key challenge involved in building a statistical automatic speech recognition (ASR) system is modeling the relationship between lexical units (that are based on subword units in the pronunciation lexicon) and acoustic feature observations. To mo ...
This research takes place in the general context of improving the performance of the Distant Speech Recognition (DSR) systems, tackling the reverberation and recognition of overlap speech. Perceptual modeling indicates that sparse representation exists in ...
In the context of hybrid HMM/MLP Automatic Speech Recognition (ASR), this paper describes an investigation into a new type of stochastic phone space transformation, which maps "source" phone (or phone HMM state) posterior probabilities (as obtained at the ...
Right-brain-damaged patients with unilateral spatial neglect are usually unaware (anosognosic) about their spatial deficits. However, in the scientific literature there is a lack of systematic and quantitative evaluation of this kind of unawareness, despit ...
In hybrid hidden Markov model/artificial neural networks (HMM/ANN) automatic speech recognition (ASR) system, the phoneme class conditional probabilities are estimated by first extracting acoustic features from the speech signal based on prior knowledge su ...
Standard hidden Markov model (HMM) based automatic speech recognition (ASR) systems use phonemes as subword units. Thus, development of ASR system for a new language or domain depends upon the availability of a phoneme lexicon in the target language. In th ...
Tracking vocal tract formant frequencies (fp) and estimating the fundamental frequency (f0) are two tracking problems that have been tackled in many speech processing works, often independently, with applications to articulatory parameters estimation ...
Institute of Electrical and Electronics Engineers2013
Posterior features have been shown to yield very good performance in multiple contexts including speech recognition, spoken term detection, and template matching. These days, posterior features are usually estimated at the output of a neural network. More ...
