Now showing items 7-13 of 13

    • Ground-Truth Transcriptions of Real Music from Force-Aligned MIDI Syntheses 

      Robert J. Turetsky; Daniel P. W. Ellis (Johns Hopkins University, 2003-10-26)
      Many modern polyphonic music transcription algorithms are presented in a statistical pattern recognition framework. But without a large corpus of real-world music transcribed at the note level, these algorithms are unable ...
    • A HMM-Based Pitch Tracker for Audio Queries 

      Nicola Orio; Matteo Sisti Sette (Johns Hopkins University, 2003-10-26)
      In this paper we present an approach to the transcription of musical queries based on a HMM. The HMM is used to model the audio features related to the singing voice, and the transcription is obtained through Viterbi ...
    • The MAMI Query-By-Voice Experiment: Collecting and annotating vocal queries for music information retrieval 

      Micheline Lesaffre; Koen Tanghe; Gaëtan Martens; Dirk Moelants; Marc Leman (Johns Hopkins University, 2003-10-26)
      The MIR research community requires coordinated strategies in dealing with databases for system development and experimentation. Manual annotated files can accelerate the development of accurate analysis tools for music ...
    • A multiple feature model for musical similarity retrieval 

      Eric Allamanche; Jürgen Herre; Oliver Hellmuth; Thorsten Kastner; Christian Ertel (Johns Hopkins University, 2003-10-26)
      Automated musical similarity search and retrieval has gained great attention in recent years, as testified by the number of proposed approaches on this topic. Despite the ``fuzzy'' nature of similarity, which varies from ...
    • Quantitative Comparisons into Content-Based Music Recognition with the Self Organising Map 

      Gavin Wood; Simon O'Keefe (Johns Hopkins University, 2003-10-26)
      With so much modern music being so widely available both in electronic form and in more traditional physical formats, a great opportunity exists for the development of a general-purpose recognition and music classification ...
    • Rhythmic Similarity through Elaboration 

      Mitchell Parry; Irfan Essa (Johns Hopkins University, 2003-10-26)
      Rhythmic similarity techniques for audio tend to evaluate how close to identical two rhythms are. This paper proposes a similarity metric based on rhythmic elaboration that matches rhythms that share the same beats regardless ...
    • A SVM ¨C Based Classification Approach to Musical Audio 

      Namunu Chinthaka Maddage; Changsheng Xu; Ye Wang (Johns Hopkins University, 2003-10-26)
      This paper describes an automatic heirarchical music classification approach based on support vector machines (SVM). Based on the proposed method, the music is classified into coursed classes such as vocal, instrumental ...