| Paper: | SLP-P14.1 | ||
| 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: | Cohort-based Speaker Model Synthesis for Channel Robust Speaker Recognition | ||
| Authors: | Wei Wu, Thomas Fang Zheng, Mingxing Xu, Tsinghua University, China | ||
| Abstract: | Speaker recognition over a public telephone network involves various types of transmission channels and handsets, which leads to mismatched channels (between the enrolled models and the test utterances), and hence to a significant decline in the speaker recognition performance. In this paper a cohort-based speaker model synthesis algorithm, which aims at synthesizing speaker models for channels where no enrollment data is available is proposed. This algorithm applies a priori knowledge of channels extracted from speaker-specific cohort sets to synthesize speaker models. Results for the China Criminal Police College (CCPC) speaker recognition corpus, which contains utterances from both a landline and a mobile channel, show significant improvements over the HT-Norm and UBM-based speaker model synthesis algorithms. | ||
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