Genetic motif discovery applied to audio analysis
Genetic motif discovery applied to audio analysis
复制标题
遗传基序发现应用于音频分析
DOI：
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发表时间：
2012
期刊：
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通讯作者：
J. Burred
中科院分区：
文献类型：
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作者：
J. Burred
模体发现算法在生物信息学中用于发现基因序列中的相关模式。在本文中，这种方法的音频分析的应用提出。在所提出的系统中，声音首先被转换成一系列离散状态，对应于特征频谱形状。然后将得到的序列进行MEME算法以进行基序发现，该算法估计每个发现的基序的结构化统计模型。该系统在两个任务中进行评估：在大型声音数据库中发现重复模式，以及在音频流中检测特定的音频事件。这两项任务都是无人监督的，并证明了该方法的可行性。
Motif discovery algorithms are used in bioinformatics to find relevant patterns in genetic sequences. In this paper, the application of such methods to audio analysis is proposed. In the presented system, sounds are first transformed into a sequence of discrete states, corresponding to characteristic spectral shapes. The resulting sequences are then subjected to the MEME algorithm for motif discovery, which estimates a structured statistical model for each found motif. The system is evaluated in two tasks: the discovery of repetitive patterns in a large sound database, and the detection of specific audio events in an audio stream. Both tasks are unsupervised and demonstrate the viability of the approach.