摘要
针对滑动变长窗口BIC算法冗余分割点多的问题,提出了基于小波子带平均能量方差和BIC的音频分割算法相结合。该算法用小波子带平均能量方差将连续音频流分割成音频段,然后用改进的滑动变长窗口BIC算法在音频段上检测声学改变点。实验表明,该算法取得了较好的分割效果,与滑动变长窗口的BIC算法相比,该算法的准确率、召回率和综合性能都得了提高。
Based on wavelet sub-band average-energy variance and Bayesian information criterion,audio segmentation algorithm is proposed,for the sliding variable-size analysis window BIC algorithm suffers from a large amount of redundancy change points.The approaches detect acoustic changes by partitioning a continuous audio stream into sub-segment using wavelet sub-band average-energy variance,and then detect acoustic changes by improved sliding variable-size analysis window BIC algorithm in sub-segment.The experiment shows that this approaches have achieved a better results,and compared with the sliding variable-size analysis window BIC algorithm,this algorithms have improved the precision,recall and F-measure.
出处
《计算机工程与应用》
CSCD
北大核心
2011年第7期139-142,共4页
Computer Engineering and Applications
基金
重庆市教育委员会科学技术研究项目资助(No.KJ080524)
关键词
小波子带能量
BIC准测
广播音频分割
准确率
召回率
wavelet sub-band energy
Bayesian Information Criterion（BIC）
broadcasting segmentation
recall
precision
