A formula to compute the similarity between two audio feature vectors is proposed, which can map arbitrary pair of vectors with equivalent dimension to [0,1）. To fulfill the task of audio segmentation, a self-similar...A formula to compute the similarity between two audio feature vectors is proposed, which can map arbitrary pair of vectors with equivalent dimension to [0,1）. To fulfill the task of audio segmentation, a self-similarity matrix is computed to reveal the inner structure of an audio clip to be segmented. As the final result must be consistent with the subjective evaluation and be adaptive to some special applications, a set of weights is adopted, which can be modified through relevance feedback techniques. Experiments show that satisfactory result can be achieved via the algorithm proposed in this paper.展开更多
Waveform audio(WAV) file is a widely used file format of uncompressed audio. With the rapid development of digital media technology, one can easily insert duplicated segments with powerful audio editing software, e.g....Waveform audio(WAV) file is a widely used file format of uncompressed audio. With the rapid development of digital media technology, one can easily insert duplicated segments with powerful audio editing software, e.g. inserting a segment of audio with negative meaning into the existing audio file. The duplicated segments can change the meaning of the audio file totally. So for a WAV file to be used as evidence in legal proceedings and historical documents, it is very importance to identify if there are any duplicated segments in it.This paper proposes a method to detect duplicated segments in a WAV file. Our method is based on the similarity calculation between two different segments. Duplicated segments are prone to having similar audio waveform,i.e., a high similarity. We use fast convolution algorithm to calculate the similarity, which makes our method quit efficient. We calculate the similarity between any two different segments in a digital audio file and use the similarity to judge which segments are duplicated. Experimental results show the feasibility and efficiency of our method on detecting duplicated audio segments.展开更多
文摘A formula to compute the similarity between two audio feature vectors is proposed, which can map arbitrary pair of vectors with equivalent dimension to [0,1）. To fulfill the task of audio segmentation, a self-similarity matrix is computed to reveal the inner structure of an audio clip to be segmented. As the final result must be consistent with the subjective evaluation and be adaptive to some special applications, a set of weights is adopted, which can be modified through relevance feedback techniques. Experiments show that satisfactory result can be achieved via the algorithm proposed in this paper.
基金the "12th Five-Year Plan" National Science and Technology Support Program(No.2012BAK16B05)
文摘Waveform audio(WAV) file is a widely used file format of uncompressed audio. With the rapid development of digital media technology, one can easily insert duplicated segments with powerful audio editing software, e.g. inserting a segment of audio with negative meaning into the existing audio file. The duplicated segments can change the meaning of the audio file totally. So for a WAV file to be used as evidence in legal proceedings and historical documents, it is very importance to identify if there are any duplicated segments in it.This paper proposes a method to detect duplicated segments in a WAV file. Our method is based on the similarity calculation between two different segments. Duplicated segments are prone to having similar audio waveform,i.e., a high similarity. We use fast convolution algorithm to calculate the similarity, which makes our method quit efficient. We calculate the similarity between any two different segments in a digital audio file and use the similarity to judge which segments are duplicated. Experimental results show the feasibility and efficiency of our method on detecting duplicated audio segments.
