Histogram Equalization to Model Adaptation for Robust Speech Recognition
<p/> <p>We propose a new model adaptation method based on the histogram equalization technique for providing robustness in noisy environments. The trained acoustic mean models of a speech recognizer are adapted into environmentally matched conditions by using the histogram equalization a...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
SpringerOpen
2010-01-01
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| Series: | EURASIP Journal on Advances in Signal Processing |
| Online Access: | http://asp.eurasipjournals.com/content/2010/628018 |
| _version_ | 1818647512997691392 |
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| author | Suh Youngjoo Kim Hoirin |
| author_facet | Suh Youngjoo Kim Hoirin |
| author_sort | Suh Youngjoo |
| collection | DOAJ |
| description | <p/> <p>We propose a new model adaptation method based on the histogram equalization technique for providing robustness in noisy environments. The trained acoustic mean models of a speech recognizer are adapted into environmentally matched conditions by using the histogram equalization algorithm on a single utterance basis. For more robust speech recognition in the heavily noisy conditions, trained acoustic covariance models are efficiently adapted by the signal-to-noise ratio-dependent linear interpolation between trained covariance models and utterance-level sample covariance models. Speech recognition experiments on both the digit-based Aurora2 task and the large vocabulary-based task showed that the proposed model adaptation approach provides significant performance improvements compared to the baseline speech recognizer trained on the clean speech data.</p> |
| first_indexed | 2024-12-17T01:03:43Z |
| format | Article |
| id | doaj.art-21dae9c3248f4bd190b2003fd2547d43 |
| institution | Directory Open Access Journal |
| issn | 1687-6172 1687-6180 |
| language | English |
| last_indexed | 2024-12-17T01:03:43Z |
| publishDate | 2010-01-01 |
| publisher | SpringerOpen |
| record_format | Article |
| series | EURASIP Journal on Advances in Signal Processing |
| spelling | doaj.art-21dae9c3248f4bd190b2003fd2547d432022-12-21T22:09:21ZengSpringerOpenEURASIP Journal on Advances in Signal Processing1687-61721687-61802010-01-0120101628018Histogram Equalization to Model Adaptation for Robust Speech RecognitionSuh YoungjooKim Hoirin<p/> <p>We propose a new model adaptation method based on the histogram equalization technique for providing robustness in noisy environments. The trained acoustic mean models of a speech recognizer are adapted into environmentally matched conditions by using the histogram equalization algorithm on a single utterance basis. For more robust speech recognition in the heavily noisy conditions, trained acoustic covariance models are efficiently adapted by the signal-to-noise ratio-dependent linear interpolation between trained covariance models and utterance-level sample covariance models. Speech recognition experiments on both the digit-based Aurora2 task and the large vocabulary-based task showed that the proposed model adaptation approach provides significant performance improvements compared to the baseline speech recognizer trained on the clean speech data.</p>http://asp.eurasipjournals.com/content/2010/628018 |
| spellingShingle | Suh Youngjoo Kim Hoirin Histogram Equalization to Model Adaptation for Robust Speech Recognition EURASIP Journal on Advances in Signal Processing |
| title | Histogram Equalization to Model Adaptation for Robust Speech Recognition |
| title_full | Histogram Equalization to Model Adaptation for Robust Speech Recognition |
| title_fullStr | Histogram Equalization to Model Adaptation for Robust Speech Recognition |
| title_full_unstemmed | Histogram Equalization to Model Adaptation for Robust Speech Recognition |
| title_short | Histogram Equalization to Model Adaptation for Robust Speech Recognition |
| title_sort | histogram equalization to model adaptation for robust speech recognition |
| url | http://asp.eurasipjournals.com/content/2010/628018 |
| work_keys_str_mv | AT suhyoungjoo histogramequalizationtomodeladaptationforrobustspeechrecognition AT kimhoirin histogramequalizationtomodeladaptationforrobustspeechrecognition |