Speaker Embedding Extraction with Phonetic Information

Autor:	Liu, Yi, He, Liang, Liu, Jia, Johnson, Michael T.
Rok vydání:	2018
Předmět:	Computer Science - Sound Electrical Engineering and Systems Science - Audio and Speech Processing
Druh dokumentu:	Working Paper
Popis:	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. Comment: submitted to Interspeech 2018 (accepted) and open-sourced. Please refer to Interspeech for the final version
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/1804.04862 Zobrazit plný text záznamu View this record from Arxiv