Open AccessProceedings Article
Feature-based approach to speech recognition.
TLDR
The alternative approach to speech recognition proposed here is based on pseudo-articulatory representations (PARs), which can be described as approximations of distinctive features, and aims to establish a mapping between them and their acoustic specifications (in this case cepstral coefficients).Abstract:
The alternative approach to speech recognition proposed here is based on pseudo-articulatory representations (PARs), which can be described as approximations of distinctive features, and aims to establish a mapping between them and their acoustic specifications (in this case cepstral coefficients). This mapping which is used as the basis for recognition is first done for vowels. It is obtained using multiple regression analysis after all the vowels have been described in terms of phonetic features and an average cepstral vector has been calculated for each of them. Based on this vowel model, the PAR values are calculated for consonants. At this point recognition is performed using a brute search mechanism to derive PAR trajectories and subsequently dynamic programming to obtain a phone sequence. The results are not as good as when hidden Markov modelling is used, but very promising taking into account the early stage of the experiments and the novelty of the approach.read more
Citations
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Knowledge-based parameters for HMM speech recognition
TL;DR: In this article, the authors presented acoustic parameters (APs) that were motivated by phonetic feature theory and employed as a signal representation of speech in a hidden Markov model (HMM) recognition framework.
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An elitist approach to automatic articulatory-acoustic feature classification for phonetic characterization of spoken language
TL;DR: The elitist framework provides a potential means of automatically annotating a corpus at the phonetic level without recourse to a word-level transcript and could thus be of utility for developing training materials for automatic speech recognition and speech synthesis applications, as well as aid the empirical study of spoken language.
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The voicing feature for stop consonants: recognition experiments with continuously spoken alphabets
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TL;DR: A two pass strategy for recognition with a hidden Markov model based first pass followed by a second pass that performs an alternative analysis using class-specific features that provides superior separability to the traditional spectral features is developed.
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Incorporating voice onset time to improve letter recognition accuracies
Partha Niyogi,Padma Ramesh +1 more
TL;DR: It is shown that a linguistically motivated acoustic feature exists (the VOT), provides superior separability to standard spectral measures, and can be automatically extracted from the signal to reduce error rates by 48.7% over state of the art HMM systems.
Proceedings Article
The design of acoustic parameters for speaker-independent speech recognition.
TL;DR: This paper presents a two-stage procedure, based on the Fisher criterion and automatic classi cation trees, for designing acoustic parameters (APs) that target phonetic features in the speech signal and shows that by basing the acoustic parameters on relative measures the impact of interspeaker variability is reduced.
References
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Journal ArticleDOI
Dynamic programming algorithm optimization for spoken word recognition
TL;DR: This paper reports on an optimum dynamic progxamming (DP) based time-normalization algorithm for spoken word recognition, in which the warping function slope is restricted so as to improve discrimination between words in different categories.
Book
A course in phonetics
TL;DR: In this paper, the authors introduce articulatory phonetics phonology and phonetic transcription, including the Consonants of English English vowels and English words and sentences, as well as the international phonetic alphabet feature hierarchy performance exercises.
Book
Phonology : a cognitive view
TL;DR: In this article, a brief introduction to linguistics and a discussion of phonology's place within that field is given. But this book assumes no previous knowledge of linguistics. And it is designed for use in first or second year phonology courses, and it will also be of value to those involved in cognitive science, neuroscience, artificial intelligence and computer science
Proceedings ArticleDOI
Syllable-level desynchronisation of phonetic features for speech recognition
TL;DR: A novel approach to speech recognition which is based on phonetic features as basic recognition units and the delayed synchronisation of these features within a higher-level prosodic domain, viz. the syllable is described.