Computer assisted pronunciation learning for English learners in Singapore
This thesis addresses the problem of modeling pronunciation variations in non-native English speech. In particular, it develops a computer assisted pronunciation learning (CAPL) system to assist speakers in Singapore to speak standard English. The dictionary of the CAPL system, also known as the lex...
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| Format: | Thesis |
| Language: | English |
| Published: |
2014
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| Online Access: | http://hdl.handle.net/10356/61565 |
| _version_ | 1811693303732633600 |
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| author | Chen, Wenda |
| author2 | Chng, Eng Siong |
| author_facet | Chng, Eng Siong Chen, Wenda |
| author_sort | Chen, Wenda |
| collection | NTU |
| description | This thesis addresses the problem of modeling pronunciation variations in non-native English speech. In particular, it develops a computer assisted pronunciation learning (CAPL) system to assist speakers in Singapore to speak standard English. The dictionary of the CAPL system, also known as the lexicon, contains the sequences of sub-word units (usually phonemes) to describe how words are pronounced. However, it is often difficult to cover all the possible pronunciations. This work presents a method to improve a given initial lexicon to include new pronunciations that can explain the pronunciation variants of regional English accents in Singapore. The method learns pronunciation rules from an orthographically transcribed speech corpus to generate common pronunciation variants. All variants are then compiled into a compact pronunciation dictionary. The upgraded dictionary are then integrated into the CAPL system, where they are used to score the user's pronunciations. The work has three novel contributions. Firstly it constructs a Singapore English corpus, which is one of the few standard corpora for speech research on the regional accent. The corpus consists of sentences used in the standard LDC TIMIT corpus. Secondly, it learns pronunciation rules from the speech data using a combination of data-driven and knowledge-based approaches in pronunciation modeling. Thirdly, it designs a prototype pronunciation scoring algorithm to evaluate and score the goodness of pronunciation in the CAPL system. The simulation shows satisfactory performance in the proposed pronunciation scoring system. |
| first_indexed | 2024-10-01T06:49:32Z |
| format | Thesis |
| id | ntu-10356/61565 |
| institution | Nanyang Technological University |
| language | English |
| last_indexed | 2024-10-01T06:49:32Z |
| publishDate | 2014 |
| record_format | dspace |
| spelling | ntu-10356/615652023-03-04T00:35:17Z Computer assisted pronunciation learning for English learners in Singapore Chen, Wenda Chng, Eng Siong Li, Haizhou School of Computer Engineering Microsoft Research Asia, Institute for Infocomm Research Centre for Computational Intelligence DRNTU::Engineering::Computer science and engineering::Software::Software engineering DRNTU::Engineering::Computer science and engineering::Computer applications::Computer-aided engineering This thesis addresses the problem of modeling pronunciation variations in non-native English speech. In particular, it develops a computer assisted pronunciation learning (CAPL) system to assist speakers in Singapore to speak standard English. The dictionary of the CAPL system, also known as the lexicon, contains the sequences of sub-word units (usually phonemes) to describe how words are pronounced. However, it is often difficult to cover all the possible pronunciations. This work presents a method to improve a given initial lexicon to include new pronunciations that can explain the pronunciation variants of regional English accents in Singapore. The method learns pronunciation rules from an orthographically transcribed speech corpus to generate common pronunciation variants. All variants are then compiled into a compact pronunciation dictionary. The upgraded dictionary are then integrated into the CAPL system, where they are used to score the user's pronunciations. The work has three novel contributions. Firstly it constructs a Singapore English corpus, which is one of the few standard corpora for speech research on the regional accent. The corpus consists of sentences used in the standard LDC TIMIT corpus. Secondly, it learns pronunciation rules from the speech data using a combination of data-driven and knowledge-based approaches in pronunciation modeling. Thirdly, it designs a prototype pronunciation scoring algorithm to evaluate and score the goodness of pronunciation in the CAPL system. The simulation shows satisfactory performance in the proposed pronunciation scoring system. Master of Engineering (SCE) 2014-06-11T08:24:36Z 2014-06-11T08:24:36Z 2014 2014 Thesis http://hdl.handle.net/10356/61565 en 68 p. application/pdf |
| spellingShingle | DRNTU::Engineering::Computer science and engineering::Software::Software engineering DRNTU::Engineering::Computer science and engineering::Computer applications::Computer-aided engineering Chen, Wenda Computer assisted pronunciation learning for English learners in Singapore |
| title | Computer assisted pronunciation learning for English learners in Singapore |
| title_full | Computer assisted pronunciation learning for English learners in Singapore |
| title_fullStr | Computer assisted pronunciation learning for English learners in Singapore |
| title_full_unstemmed | Computer assisted pronunciation learning for English learners in Singapore |
| title_short | Computer assisted pronunciation learning for English learners in Singapore |
| title_sort | computer assisted pronunciation learning for english learners in singapore |
| topic | DRNTU::Engineering::Computer science and engineering::Software::Software engineering DRNTU::Engineering::Computer science and engineering::Computer applications::Computer-aided engineering |
| url | http://hdl.handle.net/10356/61565 |
| work_keys_str_mv | AT chenwenda computerassistedpronunciationlearningforenglishlearnersinsingapore |