I-vector-based Speaker Identification with Extremely Short Utterances for Both Training and Testing

被引：0
|
作者：
Tsujikawa, Misaki [1 ]
Nishikawa, Tsuyoki [1 ]
Matsui, Tomoko [2 ]
机构：
[1] Panasonic Corp, Core Technol Elemental Dev Ctr, Kadoma, Osaka, Japan
[2] Inst Stat Math, Tachikawa, Tokyo, Japan
来源：
2017 IEEE 6TH GLOBAL CONFERENCE ON CONSUMER ELECTRONICS (GCCE) | 2017年
关键词：
Speaker identification; i-vector; Extremely short utterances;
D O I：
暂无
中图分类号：
TM [电工技术]; TN [电子技术、通信技术];
学科分类号：
0808 ; 0809 ;
摘要：
Voice applications often require the ability to make user-friendly responses by judging the user or user-type from an extremely short utterance, such as a single word. However, it is assumed that performance becomes degraded as the utterance length decreases. In this paper, we examine the performance of speaker identification for extremely short utterances of less than two seconds and then study the relationship between the accuracy and utterance length. Moreover, we show that the identification accuracy can be improved by selecting similar speakers to the target user from a large speech corpus.
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页数：4
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