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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Yingna Chen Jia liu |
| Copyright Year | 2005 |
| Description | Author affiliation: Dept. of Electron. Eng., Tsinghua Univ., Beijing, China (Yingna Chen; Jia liu) |
| Abstract | This paper describes two methods to improve the robustness of the language identification system in practical applications. One is a language model adaptation method, which modifies the language model parameters automatically to solve the mismatch problem in different channels. And the other is a confidence measure based method, which proves to be more effective comparing to conventional score based method. Experiments show that with the use of these two methods, the performance of system is greatly improved. Tested on the MCTS (multi-channel telephone speech) database, the average error rate decreases from 15.81% to 12.92% for the baseline. |
| Starting Page | 280 |
| Ending Page | 283 |
| File Size | 1823774 |
| Page Count | 4 |
| File Format | |
| ISBN | 0780395387 |
| DOI | 10.1109/ISCIT.2005.1566850 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2005-10-12 |
| Publisher Place | China |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Databases Error analysis Adaptation model Natural languages Hidden Markov models Speech recognition Telephony Robustness Computational efficiency Testing |
| Content Type | Text |
| Resource Type | Article |
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