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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Pitaksirianant, N. Saykhum, K. Wutiwiwatchai, C. Chotimongkol, A. Pimkhaokham, A. |
| Copyright Year | 2011 |
| Description | Author affiliation: Faculty of Dentistry, Chulalongkorn University, 34 Angree-dunang Rd., Pathumwan, Bangkok 10330, Thailand (Pitaksirianant, N.; Pimkhaokham, A.) || National Electronics and Computer Technology Center (NECTEC), 112 Phahonyothin Rd., Klong Nueng, Klonng Luang, Pathumthani 12120, Thailand (Saykhum, K.; Wutiwiwatchai, C.; Chotimongkol, A.) |
| Abstract | This paper introduces the use of automatic speech recognition (ASR) in speech intelligibility testing for oral surgical patients caused by cancer, tumor, or fracture. The proposed automatic system aims to help reduce the effort and cost required by the conventional human listening test. We developed a phone-based ASR system which outputs the best matched word out of a set of target words given a patient's recorded speech. To enhance the performance of the ASR system, an acoustic model is adapted toward the characteristics of each patient's voice. With an unsupervised speaker adaptation technique, the correlation between speech intelligibility scores given by the ASR system and the ones given by human judges was improved by 57% relatively. Although the overall correlation is still not sufficient for practical use at this state of the research, there is a possibility to apply the system for some specific types of patients such as fracture which the system achieved the correlation as high as 0.91. |
| Starting Page | 938 |
| Ending Page | 941 |
| File Size | 910191 |
| Page Count | 4 |
| File Format | |
| ISBN | 9781457704253 |
| e-ISBN | 9781457704246 |
| DOI | 10.1109/ECTICON.2011.5947996 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2011-05-17 |
| Publisher Place | Thailand |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Hidden Markov models Surgery Humans Speech recognition Speech Speech processing Cancer |
| Content Type | Text |
| Resource Type | Article |
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