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Search for Keywords and Vocal Elements in Audio Recordings

机译:在录音中搜索关键字和人声元素

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This paper deals with search for keywords and non-verbal vocal elements in audio recordings. An efficient detection of specific words or sounds embedded in continuous speech is based on isolated word recognition approaches. The mel-frequency cepstral coefficients and more combinations of predictive coefficients and autocorrelation coefficients were evaluated. A keyword or key sound slides along the stored speech and in each of its positions a distance (i.e., similarity) to the corresponding speech segment is computed. We found an efficient distance measure for non-verbal sound search. The average detection rates achieved 93 percent in keyword search and 74 percent in non-verbal sound search. A system developed for automatic search in audio files is presented.
机译:本文涉及在录音中搜索关键词和非语言人声元素。基于隔离的单词识别方法,可以有效检测连续语音中嵌入的特定单词或声音。评估了梅尔频率倒谱系数以及预测系数和自相关系数的更多组合。关键字或按键声音沿着存储的语音滑动,并在其每个位置中计算到相应语音段的距离(即相似度)。我们发现了一种用于非语言声音搜索的有效距离度量。关键字搜索的平均检测率达到93%,非语音搜索的平均检测率达到74%。提出了一种用于自动搜索音频文件的系统。

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