Stable-time Prediction during Incremental Speech Recognition
Chen, Xiao; Xu, Bo
2016-05
会议名称International Conference of Online Analysis and Computing Science
会议录名称Proceedings of 2016 IEEE International Conference of Online Analysis and Computing Science
会议日期28-29
会议地点Chongqing
摘要
Incremental speech recognition (ISR) is the key technology to increase the efficiency of human-computer interaction and obtain the good user experience. However, ISR’s results are not stable. The earlier methods decide whether to output the current best partial result by stable-time. These methods
can increase stability, but introduce a lag which lowers the advantage of user experience. In this paper, a new method based on the stable-time prediction is proposed. It predicts the probable stable-time of the current best partial result in the future, using the acoustic score information of N-best paths of successive frames. So it can determine whether to output the current best partial result in advance. It can reduce lags and improve performance. Results indicate that, the proposed method outperforms the baseline. At the lag of 0.2s, the proposed method results in an absolute improvement of 1.2% and achieves a stability of 92.2%. And at the other lags, the proposed method also results in a similar improvement.


 
关键词Incremental Speech Recognition Stability Lag Stable-time Prediction
文献类型会议论文
条目标识符http://ir.ia.ac.cn/handle/173211/11825
专题数字内容技术与服务研究中心_听觉模型与认知计算
通讯作者Chen, Xiao
作者单位Institute of Automation, Chinese Academy of Sciences
推荐引用方式
GB/T 7714
Chen, Xiao,Xu, Bo. Stable-time Prediction during Incremental Speech Recognition[C],2016.
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