Enhanced Phone Posteriors for Improving Speech Recognition Systems
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In this paper, we present a method for integrating possible prior knowledge (such as phonetic and lexical knowledge), as well as acoustic context (e.g., the whole utterance) in the phone posterior estimation, and we propose to use the obtained posteriors a ...
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 ...
In this paper we investigate the detection and recognition of sequences of numbers in spoken utterances. This is done in two steps: first, the entire utterance is decoded assuming that only numbers were spoken. In the second step, non-number segments (garb ...
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 ...
This paper present a principled SVM based speaker verification system. We propose a new framework and a new sequence kernel that can make use of any Mercer kernel at the frame level. An extension of the sequence kernel based on the Max operator is also pro ...
Phone posteriors has recently quite often used (as additional features or as local scores) to improve state-of-the-art automatic speech recognition (ASR) systems. Usually, better phone posterior estimates yield better ASR performance. In the present paper ...
This paper describes an approach where posterior-based features are applied in those recognition tasks where the amount of training data is insufficient to obtain a reliable estimate of the speech variability. A template matching approach is considered in ...
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 ...
In this paper we investigate the detection and recognition of sequences of numbers in spoken utterances. This is done in two steps: first, the entire utterance is decoded assuming that only numbers were spoken. In the second step, non-number segments (garb ...
This paper investigates a multilayer perceptron (MLP) based acoustic feature mapping to extract robust features for automatic speech recognition (ASR) of overlapping speech. The MLP is trained to learn the mapping from log mel filter bank energies (MFBEs) ...
