Classical Music Cover Song Retrieval System utilizing AAC Domain Features

ABSTRACT

With the rapid development of Internet and multimedia compression techniques, people can easily download or share multimedia data through networks. Therefore, efficient multimedia retrieval from huge multimedia database becomes an important issue. The most common method of search engines is through textual label. However, the label created by people may be ambiguous or even with errors. The situation like this in retrieving classical music occurs more often than pop music.

In our proposed system, we focus on classical music cover song retrieval in AAC compression domain. The modified discrete cosine transform coefficients are directly used to represent 12-dimensional chroma feature without a fully decoding process, and it can save about 70% decoding complexity. We truncate MDCT coefficients with low magnitude, adjust frequency boundary dynamically, and utilize dot-product calculation to get chroma similarity matrix. We calculate the similarity weighted arithmetic mean value between the songs by finding optimal similarity accumulated path and finally get the ranking results.

The experimental results show that the proposed method can reach Precision of 97% and save over 90% matching time compared with traditional approach in the waveform domain.