| In this paper a new, general, mathematically sound technique is developed to integrate knowledge-based information with standard cepstral features into the formal HMM framework for phoneme recognition. By using these hybrid features, the maximum amount of information contained in the speech signal can be utilised. It is shown that a trivial extension of the statistical models used to model th...

We propose to incorporate features derived using spectrotemporal receptive fields (STRFs) of neurons in the auditory cortex for phoneme recognition. Each of these STRFs is tuned to different auditory frequencies, scales and modulation rates. We select different sets of STRFs which are specific for phonemes in different broad phonetic classes (BPC) of sounds. These STRFs are then used as spectro...

In this paper we present an isolated -word recognition system using first HMM to recognize the underlying sequence of phonemes, then DP and phoneme n -gram matching techniques to determi ne the corresponding nearest idealized phoneme sequences in the dictionary. Our approach is based on the observation that there is almost a one -to-one match between phonemes and letters in the official written...

In this paper, we test the applicability of state-of-the-art automatic speech recognition (ASR) to predict phoneme confusions in human listeners. Phoneme-specific response rates are obtained from ASR based on deep neural networks (DNNs) and from listening tests with six normal-hearing subjects. The measure for model quality is the correlation of phoneme recognition accuracies obtained in ASR an...

Methods for automated vocal emotion recognition often use acoustic feature vectors that are computed for each frame in an utterance, and global statistics based on these acoustic feature vectors. However, at least two considerations argue for usage of phoneme class specific features for emotion recognition. First, there are well-known effects of phoneme class on some of these features. Second, ...

This paper deals with recurrent neural networks of multilayer perceptron type which are well-suited for speech recognition, specially for phoneme recognition. The ability of these networks has been investigated by phoneme recognition experiments using a number of Japanese words uttered by a native male speaker in a quiet environment. Results of the experiments show that recognition rates achiev...

The robustness of the ETSI (European Telecommunication Standards Institute) standardized feature extraction schemes is investigated for phoneme based recognition tasks of German speech data. The recognition tasks are an isolated command word recognition and the recognition of connected digits. The motivation of this work is the easy extensibility of a whole word recognition system by allowing a...

In the present study, we examined the distribution and processing of information over time in auditory and visual speech as it is used in unimodal and bimodal word recognition. English consonant-vowel-consonant words representing all possible initial consonants were presented as auditory, visual, or audiovisual speech in a gating task. The distribution of information over time varied across and...