A hybrid noise suppression filter for accuracy enhancement of commercial speech recognizers in varying noisy conditions
Commercial speech recognizers have made possible many speech control applications such as wheelchair, tone-phone, multifunctional robotic arms and remote controls, for the disabled and paraplegic. However, they have a limitation in common in that recognition errors are likely to be produced when bac...
| Main Authors: | , , , , |
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| Format: | Journal Article |
| Published: |
Elsevier
2014
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| Online Access: | http://hdl.handle.net/20.500.11937/27237 |
| _version_ | 1848752207750496256 |
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| author | Chan, Kit Yong, Pei Nordholm, Sven Yiu, Ka Fai Lam, H. |
| author_facet | Chan, Kit Yong, Pei Nordholm, Sven Yiu, Ka Fai Lam, H. |
| author_sort | Chan, Kit |
| building | Curtin Institutional Repository |
| collection | Online Access |
| description | Commercial speech recognizers have made possible many speech control applications such as wheelchair, tone-phone, multifunctional robotic arms and remote controls, for the disabled and paraplegic. However, they have a limitation in common in that recognition errors are likely to be produced when background noise surrounds the spoken command, thereby creating potential dangers for the disabled if recognition errors exist in the control systems. In this paper, a hybrid noise suppression filter is proposed to inter-face with the commercial speech recognizers in order to enhance the recognition accuracy under variant noisy conditions. It intends to decrease the recognition errors when the commercial speech recognizers are working under a noisy environment. It is based on a sigmoid function which can effectively enhance noisy speech using simple computational operations, while a robust estimator based on an adaptive-network-based fuzzy inference system is used to determine the appropriate operational parameters for the sigmoid function in order to produce effective speech enhancement under variant noisy conditions.The proposed hybrid noise suppression filter has the following advantages for commercial speech recognizers: (i) it is not possible to tune the inbuilt parameters on the commercial speech recognizers in order to obtain better accuracy; (ii) existing noise suppression filters are too complicated to be implemented for real-time speech recognition; and (iii) existing sigmoid function based filters can operate only in a single-noisy condition, but not under varying noisy conditions. The performance of the hybrid noise suppression filter was evaluated by interfacing it with a commercial speech recognizer, commonly used in electronic products. Experimental results show that improvement in terms of recognition accuracy and computational time can be achieved by the hybrid noise suppression filter when the commercial recognizer is working under various noisy environments in factories. |
| first_indexed | 2025-11-14T08:04:57Z |
| format | Journal Article |
| id | curtin-20.500.11937-27237 |
| institution | Curtin University Malaysia |
| institution_category | Local University |
| last_indexed | 2025-11-14T08:04:57Z |
| publishDate | 2014 |
| publisher | Elsevier |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | curtin-20.500.11937-272372019-02-19T04:27:06Z A hybrid noise suppression filter for accuracy enhancement of commercial speech recognizers in varying noisy conditions Chan, Kit Yong, Pei Nordholm, Sven Yiu, Ka Fai Lam, H. ANFIS sigmoid filter speech recognition speech enhancement commercial speech recognizer Fuzzy neural networks noise suppression filter Commercial speech recognizers have made possible many speech control applications such as wheelchair, tone-phone, multifunctional robotic arms and remote controls, for the disabled and paraplegic. However, they have a limitation in common in that recognition errors are likely to be produced when background noise surrounds the spoken command, thereby creating potential dangers for the disabled if recognition errors exist in the control systems. In this paper, a hybrid noise suppression filter is proposed to inter-face with the commercial speech recognizers in order to enhance the recognition accuracy under variant noisy conditions. It intends to decrease the recognition errors when the commercial speech recognizers are working under a noisy environment. It is based on a sigmoid function which can effectively enhance noisy speech using simple computational operations, while a robust estimator based on an adaptive-network-based fuzzy inference system is used to determine the appropriate operational parameters for the sigmoid function in order to produce effective speech enhancement under variant noisy conditions.The proposed hybrid noise suppression filter has the following advantages for commercial speech recognizers: (i) it is not possible to tune the inbuilt parameters on the commercial speech recognizers in order to obtain better accuracy; (ii) existing noise suppression filters are too complicated to be implemented for real-time speech recognition; and (iii) existing sigmoid function based filters can operate only in a single-noisy condition, but not under varying noisy conditions. The performance of the hybrid noise suppression filter was evaluated by interfacing it with a commercial speech recognizer, commonly used in electronic products. Experimental results show that improvement in terms of recognition accuracy and computational time can be achieved by the hybrid noise suppression filter when the commercial recognizer is working under various noisy environments in factories. 2014 Journal Article http://hdl.handle.net/20.500.11937/27237 10.1016/j.asoc.2013.05.017 Elsevier fulltext |
| spellingShingle | ANFIS sigmoid filter speech recognition speech enhancement commercial speech recognizer Fuzzy neural networks noise suppression filter Chan, Kit Yong, Pei Nordholm, Sven Yiu, Ka Fai Lam, H. A hybrid noise suppression filter for accuracy enhancement of commercial speech recognizers in varying noisy conditions |
| title | A hybrid noise suppression filter for accuracy enhancement of commercial speech recognizers in varying noisy conditions |
| title_full | A hybrid noise suppression filter for accuracy enhancement of commercial speech recognizers in varying noisy conditions |
| title_fullStr | A hybrid noise suppression filter for accuracy enhancement of commercial speech recognizers in varying noisy conditions |
| title_full_unstemmed | A hybrid noise suppression filter for accuracy enhancement of commercial speech recognizers in varying noisy conditions |
| title_short | A hybrid noise suppression filter for accuracy enhancement of commercial speech recognizers in varying noisy conditions |
| title_sort | hybrid noise suppression filter for accuracy enhancement of commercial speech recognizers in varying noisy conditions |
| topic | ANFIS sigmoid filter speech recognition speech enhancement commercial speech recognizer Fuzzy neural networks noise suppression filter |
| url | http://hdl.handle.net/20.500.11937/27237 |