Wei Liu

37 XueYuan Rd, Beihang University (BUAA), Beijing, P.R.China, 100191    +86-150-1110-1352



Beihang University(BUAA) 2010.9 - 2011.1

School of Automation Science and Electrical Engineering(ASEE)
Beihang University(BUAA) 2011.1 - Present

School of Advanced Engineering (SAE)


Machine Learning, Music Information Retrieval


Z. Qin, W. Liu and T. Wan, A bag-of-tones model with MFCC features for musical genre classification, ADMA 2013, Springer.


2012.8 — Present    Research Student
Intelligent Computing and Machine Learning Lab, Beihang University, Beijing, China
  Advisor: Prof. Zengchang Qin (Associate Professor)
  Topic: Music Information Retrieval, Music genre classification


  • Music genre classification

  •   2012.8-Present

      Intelligent Computing and Machine Learning Lab, ASEE, Beihang University

    We proposed a new model for music genre classification. The model is referred to as The Bag-of-Tones (BOT) model which follows the conceptually similar idea of the bag-of-words(BOW) model in natural language processing and the bag-of-feature(BOF) model in image processing. The basic low-level music features such as Mel-frequency cepstral coefficients (MFCC) are clustered into a set of codewords referred to as "tones". By using such a model, each piece of music can be represented by a new feature vector of distribution on tones. Classical machine learning models such as support vector machines (SVM) can be applied for genre classification. By comparing to the previous work, we found the new proposed model outperform classical models on a given benchmark dataset. In general, this model can be used to structure the large collections of music available on the web. It can play an important role in automatic music categorization and retrieval.

    [Download BUAA5 Dataset] <It could be too big to be downloaded, please contact me if you hope to test on the data!>

    [Download GTZAN Dataset]


    • Second Prize in Beijing, Contempopary Undergraduate Mathematical Contest In Modeling, China 2012


    • Proficient in C/C++, matlab,python;

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