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  1. Proceedings of the 1st international ACM workshop on Music information retrieval with user-centered and multimodal strategies (MIRUM '11)
  2. Music identification via vocabulary tree with MFCC peaks
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The need for music information retrieval with user-centered and multimodal strategies
Audiovisual archive exploitation in the networked information society
Music identification via vocabulary tree with MFCC peaks
Analyzing sound tracings: a multimodal approach to music information retrieval
Affective content analysis of music video clips
Finding geographically representative music via social media
Advantages of nonstationary gabor transforms in beat tacking
A tempo-sensitive music search engine with multimodal inputs
Music genre classification using explicit semantic analysis
A musical mood trajectory estimation method using lyrics and acoustic features
What is a "Musical World"? An affinity propagation approach

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Music identification via vocabulary tree with MFCC peaks

Content Provider ACM Digital Library
Author Yu, Adams Wei Lang, Bo Xu, Tianjing Liu, Xianglong
Abstract In this paper, a Vocabulary Tree based framework is proposed for music identification whose target is to recognize a fragment from a song database. The key to a high recognition precision within this framework is a novel feature, namely MFCC Peaks, which is a combination of MFCC and Spectral Peaks features. Our approach consists of three stages. We first build the Vocabulary Tree with 2 million MFCC Peaks features extracted from hundreds of music. Then each song in the database is quantified into some words by traveling from root down to a certain leaf. Given a query input, we apply the same quantization procedure to this fragment, score the archive according to the TF-IDF scheme and return the best matches. The experimental results demonstrate that our proposed feature has strong identifying and generalization ability. Other trials show that our approach scales well with the size of database. Further comparison also demonstrates that while our algorithm achieves approximately the same retrieval precision as other state-of-the-art methods, it cost less time and memory.
Starting Page 21
Ending Page 26
Page Count 6
File Format PDF
ISBN 9781450309868
DOI 10.1145/2072529.2072537
Language English
Publisher Association for Computing Machinery (ACM)
Publisher Date 2011-11-30
Publisher Place New York
Access Restriction Subscribed
Subject Keyword Mfcc peaks Vocabulary tree Music identification
Content Type Text
Resource Type Article
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