Improving the Multi-Stack Decoding Algorithm in a Segment-based Speech Recognizer
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| Title: | Improving the Multi-Stack Decoding Algorithm in a Segment-based Speech Recognizer |
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| Authors: | Gábor Gosztolya, András Kocsor |
| Contributors: | The Pennsylvania State University CiteSeerX Archives |
| Source: | http://www.inf.u-szeged.hu/~kocsor/publications/Papers/2003/Conf-2003-LNCS-IEA-AIE-GG/Web/GKo03.pdf. |
| Publisher Information: | Springer Verlag |
| Publication Year: | 2003 |
| Collection: | CiteSeerX |
| Description: | During automatic speech recognition selecting the best hypothesis over a combinatorially huge hypothesis space is a very hard task, so selecting fast and efficient heuristics is a reasonable strategy. In this paper a general purpose heuristic, the multi-stack decoding method, was refined in several ways. For comparison, these improved methods were tested along with the well-known Viterbi beam search algorithm on a Hungarian number recognition task where the aim was to minimize the scanned hypothesis elements during the search process. The test showed that our method runs 6 times faster than the basic multi-stack decoding method, and 9 times faster than the Viterbi beam search method. |
| Document Type: | text |
| File Description: | application/pdf |
| Language: | English |
| Relation: | http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.95.4366 |
| Availability: | http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.95.4366 http://www.inf.u-szeged.hu/~kocsor/publications/Papers/2003/Conf-2003-LNCS-IEA-AIE-GG/Web/GKo03.pdf |
| Rights: | Metadata may be used without restrictions as long as the oai identifier remains attached to it. |
| Accession Number: | edsbas.D9C72C2D |
| Database: | BASE |
Nájsť tento článok vo Web of Science | Abstract: | During automatic speech recognition selecting the best hypothesis over a combinatorially huge hypothesis space is a very hard task, so selecting fast and efficient heuristics is a reasonable strategy. In this paper a general purpose heuristic, the multi-stack decoding method, was refined in several ways. For comparison, these improved methods were tested along with the well-known Viterbi beam search algorithm on a Hungarian number recognition task where the aim was to minimize the scanned hypothesis elements during the search process. The test showed that our method runs 6 times faster than the basic multi-stack decoding method, and 9 times faster than the Viterbi beam search method. |
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