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Proceedings ArticleDOI

Speaker independent digit recognition with reference frame-specific distance measures

E. Bocchieri, +1 more
- Vol. 11, pp 2699-2702
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TLDR
This work defines novel distance measures for speech recognition which are specifically designed to differentiate between confusable speech sounds.
Abstract
This work defines novel distance measures for speech recognition which: 1. Model the statistical interaction between adjacent speech frames, 2. Model the statistical characteristics of different speech sounds individually, 3. Are specifically designed to differentiate between confusable speech sounds. Speaker independent recognition tests performed on the Texas Instruments multi-dialect isolated digit data base give substitution rates as low as 0.6 % with a vocabulary of 11 digits.

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Citations
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Journal ArticleDOI

The application of dynamic programming to connected speech recognition

TL;DR: Principles of dynamic programming and its application to discrete-utterance and connected-speech recognition are introduced and discussed, and the deterministic form, used for template matching for connected speech, is described in detail.

Real-time recognition of spoken words

TL;DR: In this article, a real-time word recognition system using only a small computer (8K memory) and a few analog peripherals is described, where a spectral analysis is carried out by a bank of 17 1/3-octave bandpass filters.
Dissertation

Natural language processing for resource-poor languages

Long Duong
TL;DR: Transfer learning provides an important opportunity for low-resource NLP, whereby annotation is transferred from a source resource-rich language to a target resource poor-language, and is successfully applied in this thesis.
Proceedings ArticleDOI

Outlier Correction for Local Distance Measures in Example Based Speech Recognition

TL;DR: Two techniques inspired by non-parametric density estimation that explicitly adjust the distance measure based on the position of the reference vector in its class are derived.
Journal ArticleDOI

Speech recognition using hidden Markov models based on segmental statistics

TL;DR: The results show that utilization of segmental features as input vectors to basic HMMs gave us better recognition rates than those by the traditional methods, and integration of regression coefficients into the segmental unit HMMs yielded the best results.
References
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Book

Pattern recognition principles

TL;DR: The present work gives an account of basic principles and available techniques for the analysis and design of pattern processing and recognition systems.
Proceedings ArticleDOI

A database for speaker-independent digit recognition

TL;DR: A large speech database has been collected for use in designing and evaluating algorithms for speaker independent recognition of connected digit sequences and formal human listening tests on this database provided certification of the labelling of the digit sequences.
Journal ArticleDOI

Considerations in dynamic time warping algorithms for discrete word recognition

TL;DR: It is shown that, based on a set of assumptions about the distributions of the distances, the warping algorithm that minimizes the overall probability of making a word error is the modified time Warping algorithm with unconstrained endpoints.
Journal ArticleDOI

Speaker-independent recognition of isolated words using clustering techniques

TL;DR: A speaker-independent isolated word recognition system is described which is based on the use of multiple templates for each word in the vocabulary, and shows error rates that are comparable to, or better than, those obtained with speaker-trained isolatedword recognition systems.
Journal ArticleDOI

Considerations in dynamic time warping algorithms for discrete word recognition

TL;DR: An algorithm in which an uncertainty exists in the registration both for initial and final frames was studied and another which constrains the dynamic path to follow the path which is locally minimum at each frame.
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