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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Phu Chien Nguyen Akagi, M. Tu Bao Ho |
| Copyright Year | 2003 |
| Description | Author affiliation: Japan Adv. Inst. of Sci. & Technol., Ishikawa, Japan (Phu Chien Nguyen; Akagi, M.; Tu Bao Ho) |
| Abstract | A new set of features is proposed that has been found to improve the performance of automatic speaker identification systems. The new set of features is referred to as "event targets". The new features have been derived from line spectral frequency (LSF) parameters using the so-called "temporal decomposition" (TD) technique. The number of feature vectors required for both the training and testing phases has been reduced by one-fifth compared to that of the traditional Mel-frequency cepstrum coefficients (MFCC) features, while the identification results obtained are comparable or even better. Also, we introduce one more application of TD (speaker recognition) in addition to speech coding, speech segmentation, and speech recognition. It shows that the event targets in TD can convey information about the identity of a speaker. |
| Sponsorship | IEEE Signal Process, Soc |
| File Size | 337172 |
| File Format | |
| ISBN | 0780376633 |
| ISSN | 15206149 |
| DOI | 10.1109/ICASSP.2003.1198747 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2003-04-06 |
| Publisher Place | China |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Speaker recognition Feature extraction Hidden Markov models Testing Speech coding Spectral analysis Vector quantization Cepstrum Mel frequency cepstral coefficient Speech recognition |
| Content Type | Text |
| Resource Type | Article |
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