| Paper: | SLP-P14.8 | ||
| Session: | Speaker Recognition: Models and Methods | ||
| Time: | Thursday, May 18, 14:00 - 16:00 | ||
| Presentation: | Poster | ||
| Topic: | Speech and Spoken Language Processing: Speaker Verification | ||
| Title: | Syllable Lattice Based Re-scoring for Speaker Verification | ||
| Authors: | Minho Jin, Korea Advanced Institute of Science and Technology, Republic of Korea; Frank K. Soong, Microsoft Research Asia, China; Chang D. Yoo, Korea Advanced Institute of Science and Technology, Republic of Korea | ||
| Abstract: | The Gaussian mixture based GMM-UBM approaches have shown good performance in speaker verification without using contextual information. In this paper, we exploit the information provided in the arcs of a decoded syllable lattice for speaker verification. The forward algorithm is used to summarize this information in the syllable lattice instead of the best decoded string. The performance is evaluated on a Mandarin Chinese database. With two minutes of target speaker's enrollment data, the proposed algorithm shows 1.03% of equal-error rate for short input utterances with an average duration of two seconds. By combining with the GMM-UBM, the system shows a 0.74% of equal-error rate. | ||
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