电子学报2018，Vol.46Issue(4)：878-885,8.DOI:10.3969/j.issn.0372-2112.2018.04.016
基于长时信息的自适应话音激活检测
Adaptive Voice Activity Detection Based on Long-Term Information
摘要
Abstract
The long-term information of speech signals shows excellent performances in the applications of voice activity detection.Six types of long-term information based on auditory filter banks are proposed through the non-linear spectral decomposition with three different auditory filters.Further,an adaptive voice activity detection algorithm based on these types of long-term information is proposed.Without additional training data,this algorithm use the data selecting from the test signals according to long-term information to train a speech/non-speech classifier,and classifies the current test signals using the speech/non-speech classifier frame by frame.Experiments on TIMIT dataset and NOISEX-92 dataset show that the algorithm improves the performance of VAD with higher accuracy and stronger robustness in low SNR noisy environments.The online experiments show that it can also obtain a good performance in real-time processing conditions.关键词
话音激活检测/长时信息/听觉滤波器/自适应Key words
voice activity detection/long-term information/auditory filter bank/adaptive分类
信息技术与安全科学引用本文复制引用
杨绪魁,屈丹,张文林,闫红刚..基于长时信息的自适应话音激活检测[J].电子学报,2018,46(4):878-885,8.基金项目
国家自然科学基金(No.61673395,No.61403415) （No.61673395,No.61403415）
河南省自然科学基金(No.162300410331) （No.162300410331）
