Speaker Embedding Extraction with Phonetic Information
FOS: Computer and information sciences
Sound (cs.SD)
03 medical and health sciences
Audio and Speech Processing (eess.AS)
FOS: Electrical engineering, electronic engineering, information engineering
0202 electrical engineering, electronic engineering, information engineering
02 engineering and technology
0305 other medical science
Computer Science - Sound
Electrical Engineering and Systems Science - Audio and Speech Processing
DOI:
10.21437/interspeech.2018-1226
Publication Date:
2018-08-28T09:55:42Z
AUTHORS (4)
ABSTRACT
submitted to Interspeech 2018 (accepted) and open-sourced. Please refer to Interspeech for the final version<br/>Speaker embeddings achieve promising results on many speaker verification tasks. Phonetic information, as an important component of speech, is rarely considered in the extraction of speaker embeddings. In this paper, we introduce phonetic information to the speaker embedding extraction based on the x-vector architecture. Two methods using phonetic vectors and multi-task learning are proposed. On the Fisher dataset, our best system outperforms the original x-vector approach by 20% in EER, and by 15%, 15% in minDCF08 and minDCF10, respectively. Experiments conducted on NIST SRE10 further demonstrate the effectiveness of the proposed methods.<br/>
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