Chroma Binary Similarity and Local Alignment Applied to Cover Song Identification
نویسندگان
چکیده
منابع مشابه
Improving Binary Similarity and Local Alignment for Cover Song Detection
This is an extended abstract that overviews our cover song detection system as submitted to the MIREX 2008 audio cover song identification task. The system is developed starting from our 2007 submission but includes some important modifications and parameter tuning. Our system obtains the best results in all evaluation measures considered and its accuracy is proved to be statistically significa...
متن کاملCover Song Identification Based on Similarity Fusion
We describe a similarity fusion based cover song identification scheme. The Harmonic Pitch Class Profile (HPCP) is chosen as the musical descriptor. First, the similarity between HPCP descriptors of two songs are obtained based on Qmax function and Dmax function, respectively. Then these two similarities are fused via Similarity Network Fusion (SNF) technique, which was originally proposed for ...
متن کاملTwo-layer similarity fusion model for cover song identification
Various musical descriptors have been developed for Cover Song Identification (CSI). However, different descriptors are based on various assumptions, designed for representing distinct characteristics of music, and often differ in scale and noise level. Therefore, a single similarity function combined with a specific descriptor is generally not able to describe the similarity between songs comp...
متن کاملA Chroma-based Tempo-insensitive Distance Measure for Cover Song Identification
In the context of music, a cover version is a remake of a song, often with significant stylistic variation. In this paper we describe a distance measure between sampled audio files that is designed to be insensitive to instrumentation, time shift, temporal scaling and transpositions. The algorithm was submitted to the Music Information Retrieval eXchange (MIREX) 2007 audio cover song identifica...
متن کاملCombining Chroma Features For Cover Version Identification
We present an approach for cover version identification which is based on combining different discretized features derived from the chromagram vectors extracted from the audio data. For measuring similarity between features, we use a parameter-free quasi-universal similarity metric which utilizes data compression. Evaluation proves that combined feature distances increase the accuracy in cover ...
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ژورنال
عنوان ژورنال: IEEE Transactions on Audio, Speech, and Language Processing
سال: 2008
ISSN: 1558-7916
DOI: 10.1109/tasl.2008.924595