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The use of speed-up techniques for a speech recognizer system.

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Bibliographic Details
Title: The use of speed-up techniques for a speech recognizer system.
Authors: Kocsor, András, Gosztolya, Gábor
Source: International Journal of Speech Technology; Sep2007, Vol. 9 Issue 3/4, p95-107, 13p, 5 Charts, 4 Graphs
Subject Terms: AUTOMATIC speech recognition, SPEECH perception, TIME, PERCEPTRONS, PATTERN recognition systems, COMPUTER input-output equipment
Abstract: In speech recognition, not just the accuracy of an automatic speech recognition application is important, but also its speed. However, if we want to create a real-time speech recognizer, this requirement limits the time that is spent on searching for the best hypothesis, which can even affect the recognition accuracy. Thus the applied search method plays an important role in the speech recognition task, and so does its efficiency, i.e. how quickly it finds the uttered words. To speed up this search process, various ideas are available in the literature: we can use search heuristics, multi-pass search, or apply a family of aggregation operators. In this paper we test all these methods in turn, and combine them with a set of other novel speed-up ideas. The test results confirm that all of these techniques are valuable: using combinations of them helped make the speech recognition process over 12 times faster than the basic multi-stack decoding algorithm, and almost 11 times faster than the Viterbi beam search method. [ABSTRACT FROM AUTHOR]
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Database: Complementary Index
Description
Abstract:In speech recognition, not just the accuracy of an automatic speech recognition application is important, but also its speed. However, if we want to create a real-time speech recognizer, this requirement limits the time that is spent on searching for the best hypothesis, which can even affect the recognition accuracy. Thus the applied search method plays an important role in the speech recognition task, and so does its efficiency, i.e. how quickly it finds the uttered words. To speed up this search process, various ideas are available in the literature: we can use search heuristics, multi-pass search, or apply a family of aggregation operators. In this paper we test all these methods in turn, and combine them with a set of other novel speed-up ideas. The test results confirm that all of these techniques are valuable: using combinations of them helped make the speech recognition process over 12 times faster than the basic multi-stack decoding algorithm, and almost 11 times faster than the Viterbi beam search method. [ABSTRACT FROM AUTHOR]
ISSN:13812416
DOI:10.1007/s10772-008-9005-5