Proceedings ArticleDOI
Lexicon-building methods for an acoustic sub-word based speech recognizer
Kuldip K. Paliwal
- Vol. 1990, pp 729-732
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TLDR
The use of an acoustic subword unit (ASWU)-based speech recognition system for the recognition of isolated words is discussed and it is shown that the use of a modified k-means algorithm on the likelihoods derived through the Viterbi algorithm provides the best deterministic-type of word lexicon.Abstract:
The use of an acoustic subword unit (ASWU)-based speech recognition system for the recognition of isolated words is discussed. Some methods are proposed for generating the deterministic and the statistical types of word lexicon. It is shown that the use of a modified k-means algorithm on the likelihoods derived through the Viterbi algorithm provides the best deterministic-type of word lexicon. However, the ASWU-based speech recognizer leads to better performance with the statistical type of word lexicon than with the deterministic type. Improving the design of the word lexicon makes it possible to narrow the gap in the recognition performances of the whole word unit (WWU)-based and the ASWU-based speech recognizers considerably. Further improvements are expected by designing the word lexicon better. >read more
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Book ChapterDOI
Toward ALISP: A proposal for Automatic Language Independent Speech Processing
Gérard Chollet,Jan Cernocký,Andrei Constantinescu,Sabine Deligne,Sabine Deligne,Frédéric Bimbot +5 more
TL;DR: This article exposes and develops the concept of ALISP (Automatic Language Independent Speech Processing), namely a general methodology which consists in inferring the intermediate representation between the acoustic and the linguistic levels, from speech and linguistic data rather than from a priori knowledge, with as little supervision as possible.
Book
Statistical Pronunciation Modeling for Non-Native Speech Processing
TL;DR: This work presents a fully statistical approach to model non--native speakers' pronunciation, based on a discrete hidden Markov model as a word pronunciation model, initialized on a standard pronunciation dictionary.
Learning features and segments from waveforms : a statistical model of early phonological acquisition
TL;DR: Of the Dissertation Learning Features and Segments from Waveforms: A Statistical Model of Early Phonological Acquisition and its Applications.
Dissertation
Unsupervised pattern discovery in speech: applications to word acquisition and speaker segmentation
James Glass,Alex Park +1 more
TL;DR: It is shown how pattern discovery can be used to automatically acquire lexical entities directly from an untranscribed audio stream, and two methods for automatically identifying sound clusters generated through pattern discovery are proposed and evaluated.
Proceedings ArticleDOI
Design of a speech recognition system based on acoustically derived segmental units
TL;DR: An iterative unit design procedure is formulated which consistently uses a maximum likelihood (ML) objective in successive application of resegmentation and model re-estimation.
References
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A Maximum Likelihood Approach to Continuous Speech Recognition
TL;DR: This paper describes a number of statistical models for use in speech recognition, with special attention to determining the parameters for such models from sparse data, and describes two decoding methods appropriate for constrained artificial languages and one appropriate for more realistic decoding tasks.
Proceedings ArticleDOI
Acoustic Markov models used in the Tangora speech recognition system
TL;DR: An automatic technique for constructing Markov word models is described and results are included of experiments with speaker-dependent and speaker-independent models on several isolated-word recognition tasks.
Journal ArticleDOI
A modified K-means clustering algorithm for use in isolated work recognition
TL;DR: A clustering algorithm based on a standard K-means approach which requires no user parameter specification is presented and experimental data show that this new algorithm performs as well or better than the previously used clustering techniques when tested as part of a speaker-independent isolated word recognition system.