Speech feature smoothing for robust ASR
65 p.
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2014
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| Online Access: | http://hdl.handle.net/10356/58086 |
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| Institution: | Nanyang Technological University |
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sg-ntu-dr.10356-580862023-07-04T16:12:42Z Speech feature smoothing for robust ASR Sinduja Subbhuraam Soon Ing Yann School of Electrical and Electronic Engineering DRNTU::Engineering::Electrical and electronic engineering 65 p. Speech enhancement module is the key component in noise robust Automatic Speech Recognizer. A number of research studies have been conducted to improve the recognition accuracy of the Automatic Speech Recognizer. In this work, an attempt has been made to develop one such speech enhancement technique that is based on the existing popular technique called the Stereo-based Piecewise Linear Compensation for Environments. This report presents the review of the literature related to this work. It also describes the proposed methodology, and presents the results obtained using the same on the benchmark speech database called the Aurora2. The results show that the proposed algorithm is capable of achieving better accuracy than that obtained for basic Stereo-based Piecewise Linear Compensation for Environments algorithm. Master of Science (Signal Processing) 2014-04-07T12:13:43Z 2014-04-07T12:13:43Z 2011 2011 Thesis http://hdl.handle.net/10356/58086 Nanyang Technological University application/pdf |
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DRNTU::Engineering::Electrical and electronic engineering Sinduja Subbhuraam Speech feature smoothing for robust ASR |
| description |
65 p. |
| author2 |
Soon Ing Yann |
| author_facet |
Soon Ing Yann Sinduja Subbhuraam |
| format |
Theses and Dissertations |
| author |
Sinduja Subbhuraam |
| author_sort |
Sinduja Subbhuraam |
| title |
Speech feature smoothing for robust ASR |
| title_short |
Speech feature smoothing for robust ASR |
| title_full |
Speech feature smoothing for robust ASR |
| title_fullStr |
Speech feature smoothing for robust ASR |
| title_full_unstemmed |
Speech feature smoothing for robust ASR |
| title_sort |
speech feature smoothing for robust asr |
| publishDate |
2014 |
| url |
http://hdl.handle.net/10356/58086 |
| _version_ |
1772826732556976128 |