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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Chongjia Ni Cheung-Chi Leung |
| Copyright Year | 2014 |
| Description | Author affiliation: Inst. for Infocomm Res. (I2R), A*STAR, Singapore, Singapore (Chongjia Ni; Cheung-Chi Leung) |
| Abstract | Chinese word segmentation (CWS) is a necessary step in Mandarin Chinese automatic speech recognition (ASR), and it has an impact on the results of ASR. However, there are few works on the relations between CWS and ASR. CWS settings, including segmentation standards and algorithms, are involved in building a segmenter. In this paper, four CWS standards and three CWS algorithms, including maximum matching, term frequency based and conditional random field (CRF) based algorithms, are investigated for ASR performance. Our experiments on the second Sighan Bakeoff data and Mandarin Chinese conversational telephone speech show that a better segmentation performance does not necessarily lead to a better ASR performance. Maximum matching and the term frequency based algorithm, which are classified as lexicon-based algorithms, are more flexible to update their vocabulary inventories according to the application need. We find that these two algorithms can provide similar ASR performance as the CRF-based algorithm. Motivated by the availability of huge amounts of web text data, we investigate whether this can improve the term frequency based algorithm and thus the ASR performance. Lastly we find that combining the two lexicon-based algorithms through language model interpolation can further improve the ASR performance. |
| Starting Page | 44 |
| Ending Page | 48 |
| File Size | 151565 |
| Page Count | 5 |
| File Format | |
| ISBN | 9781479942190 |
| DOI | 10.1109/ISCSLP.2014.6936684 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2014-09-12 |
| Publisher Place | Singapore |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Training Computational modeling Training data Speech Data models Classification algorithms Chinese word segmentation automatic speech recognition Chinese word segmentation combination Standards |
| Content Type | Text |
| Resource Type | Article |
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