Combining Chroma Features For Cover Version Identification
نویسنده
چکیده
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 version identification.
منابع مشابه
Combining Features for Cover Song Identification
In this paper, we evaluate a set of methods for combining features for cover song identification. We first create multiple classifiers based on global tempo, duration, loudness, beats and chroma average features, training a random forest for each feature. Subsequently, we evaluate standard combination rules for merging these single classifiers into a composite classifier based on global feature...
متن کاملEnhancing Cover Song Identification with Hierarchical Rank Aggregation
Cover song identification involves calculating pairwise similarities between a query audio track and a database of reference tracks. While most authors make exclusively use of chroma features, recent work tends to demonstrate that combining similarity estimators based on multiple audio features increases the performance. We improve this approach by using a hierarchical rank aggregation method f...
متن کاملClassifying Music Audio with Timbral and Chroma Features
Music audio classification has most often been addressed bymodeling the statistics of broad spectral features, which, by design, exclude pitch information and reflect mainly instrumentation. We investigate using instead beat-synchronous chroma features, designed to reflect melodic and harmonic content and be invariant to instrumentation. Chroma features are less informative for classes such as ...
متن کاملBLAST for Audio Sequences Alignment: A Fast Scalable Cover Identification Tool
Searching for similarities in largemusical databases is common for applications such as cover song identification. These methods typically use dynamic programming to align the shared musical motifs between subparts of two recordings. Such music local alignment methods are slow, as are the bioinformatics algorithms they are closely related to. We have adapted the ideas of the Basic Local Alignme...
متن کاملIdentifying ‘Cover Songs’ with Beat-Synchronous Chroma Features
Large music collections, ranging from thousands to millions of tracks, are unsuited to manual searching, motivating the development of automatic search methods. When two musical groups perform the same underlying song or piece, these are known as ‘cover’ versions. We describe a system that attempts to identify such a relationship between music audio recordings. To overcome variability in tempo,...
متن کامل