A Framework For Automatic Code Switching Speech Recognition With Multilingual Acoustic And Pronunciation Models Adaptation
Recognition of code-switching speech is a challenging problem because of three issues. Code-switching is not a simple mixing of two languages, but each has its own phonological, lexical, and grammatical variations. Second, code-switching resources, such as speech and text corpora, are limited and...
| Main Author: | |
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| Format: | Thesis |
| Language: | English |
| Published: |
2014
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| Subjects: | |
| Online Access: | http://eprints.usm.my/62374/ http://eprints.usm.my/62374/1/24%20Pages%20from%2000001780802.pdf |
| _version_ | 1848884966322077696 |
|---|---|
| author | Ahmed, Basem H. A. |
| author_facet | Ahmed, Basem H. A. |
| author_sort | Ahmed, Basem H. A. |
| building | USM Institutional Repository |
| collection | Online Access |
| description | Recognition of code-switching speech is a challenging problem because of three issues.
Code-switching is not a simple mixing of two languages, but each has its own
phonological, lexical, and grammatical variations. Second, code-switching resources, such
as speech and text corpora, are limited and difficult to collect. Therefore, creating codeswitching
speech recognition models may require a different strategy from that typically
used for monolingual automatic speech recognition (ASR). Third, a segment of language
switching in an utterance can be as short as a word or as long as an utterance itself. This
variation may make language identification difficult. In this thesis, we propose a novel
approach to achieve automatic recognition of code-switching speech. The proposed
method consists of two phases, namely, ASR and rescoring. The framework uses parallel
automatic speech recognizers for speech recognition. We also put forward the usage of an
acoustic model adaptation approach known as hybrid approach of interpolation and
merging to cross-adapt acoustic models of different languages to recognize code-switching
speech better. In pronunciation modeling, we propose an approach to model the
pronunciation of non-native accented speech for an ASR system. Our approach is tested on
two code-switching corpora: Malay-English and Mandarin-English. |
| first_indexed | 2025-11-15T19:15:06Z |
| format | Thesis |
| id | usm-62374 |
| institution | Universiti Sains Malaysia |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-15T19:15:06Z |
| publishDate | 2014 |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | usm-623742025-05-29T01:44:31Z http://eprints.usm.my/62374/ A Framework For Automatic Code Switching Speech Recognition With Multilingual Acoustic And Pronunciation Models Adaptation Ahmed, Basem H. A. QA75.5-76.95 Electronic computers. Computer science Recognition of code-switching speech is a challenging problem because of three issues. Code-switching is not a simple mixing of two languages, but each has its own phonological, lexical, and grammatical variations. Second, code-switching resources, such as speech and text corpora, are limited and difficult to collect. Therefore, creating codeswitching speech recognition models may require a different strategy from that typically used for monolingual automatic speech recognition (ASR). Third, a segment of language switching in an utterance can be as short as a word or as long as an utterance itself. This variation may make language identification difficult. In this thesis, we propose a novel approach to achieve automatic recognition of code-switching speech. The proposed method consists of two phases, namely, ASR and rescoring. The framework uses parallel automatic speech recognizers for speech recognition. We also put forward the usage of an acoustic model adaptation approach known as hybrid approach of interpolation and merging to cross-adapt acoustic models of different languages to recognize code-switching speech better. In pronunciation modeling, we propose an approach to model the pronunciation of non-native accented speech for an ASR system. Our approach is tested on two code-switching corpora: Malay-English and Mandarin-English. 2014-05 Thesis NonPeerReviewed application/pdf en http://eprints.usm.my/62374/1/24%20Pages%20from%2000001780802.pdf Ahmed, Basem H. A. (2014) A Framework For Automatic Code Switching Speech Recognition With Multilingual Acoustic And Pronunciation Models Adaptation. PhD thesis, Perpustakaan Hamzah Sendut. |
| spellingShingle | QA75.5-76.95 Electronic computers. Computer science Ahmed, Basem H. A. A Framework For Automatic Code Switching Speech Recognition With Multilingual Acoustic And Pronunciation Models Adaptation |
| title | A Framework For Automatic Code Switching Speech Recognition With Multilingual Acoustic And Pronunciation Models Adaptation |
| title_full | A Framework For Automatic Code Switching Speech Recognition With Multilingual Acoustic And Pronunciation Models Adaptation |
| title_fullStr | A Framework For Automatic Code Switching Speech Recognition With Multilingual Acoustic And Pronunciation Models Adaptation |
| title_full_unstemmed | A Framework For Automatic Code Switching Speech Recognition With Multilingual Acoustic And Pronunciation Models Adaptation |
| title_short | A Framework For Automatic Code Switching Speech Recognition With Multilingual Acoustic And Pronunciation Models Adaptation |
| title_sort | framework for automatic code switching speech recognition with multilingual acoustic and pronunciation models adaptation |
| topic | QA75.5-76.95 Electronic computers. Computer science |
| url | http://eprints.usm.my/62374/ http://eprints.usm.my/62374/1/24%20Pages%20from%2000001780802.pdf |