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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Hansen, J.H.L. Arslan, L.M. |
| Copyright Year | 1995 |
| Description | Author affiliation: Dept. of Electr. Eng., Duke Univ., Durham, NC, USA (Hansen, J.H.L.; Arslan, L.M.) |
| Abstract | Speaker accent is an important issue in the formulation of robust speaker independent recognition systems. Knowledge gained from a reliable accent classification approach could improve overall recognition performance. In this paper, a new algorithm is proposed for foreign accent classification of American English. A series of experimental studies are considered which focus on establishing how speech production is varied to convey accent. The proposed method uses a source generator framework, recently proposed for analysis and recognition of speech under stress [5]. An accent sensitive database is established using speakers of American English with foreign language accents. An initial version of the classification algorithm classified speaker accent from among four different accents with an accuracy of 81.5% in the case of unknown text, and 88.9% assuming known text. Finally, it is shown that as ascent sensitive word count increases, the ability to correctly classify accent also increases, achieving an overall classification rate of 92% among four accent classes. |
| Starting Page | 836 |
| Ending Page | 839 |
| File Size | 693754 |
| Page Count | 4 |
| File Format | |
| ISBN | 0780324315 |
| ISSN | 15206149 |
| DOI | 10.1109/ICASSP.1995.479824 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 1995-05-09 |
| Publisher Place | USA |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Speech recognition Natural languages Robustness Speech analysis Rhythm Speech processing Laboratories Databases Classification algorithms Stress |
| Content Type | Text |
| Resource Type | Article |
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