Now showing items 1-13 of 13

    • Application of missing feature theory to the recognition of musical instruments in polyphonic audio 

      Jana Eggink; Guy J. Brown (Johns Hopkins University, 2003-10-26)
      A system for musical instrument recognition based on a Gaussian Mixture Model (GMM) classifier is introduced. To enable instrument recognition when more than one sound is present at the same time, ideas from missing feature ...
    • Automatic Labelling of Tabla Signals 

      Olivier Gillet; Gaël Richard (Johns Hopkins University, 2003-10-26)
      Most of the recent developments in the field of music indexing and music information retrieval are focused on western music. In this paper, we present an automatic music transcription system dedicated to Tabla - a North ...
    • Automatic Synchronization of Music Data in Score-, MIDI- and PCM-Format 

      Vlora Arifi; Michael Clausen; Frank Kurth; Meinard Müller (Johns Hopkins University, 2003-10-26)
      In this paper we present algorithms for the automatic time-synchronization of score-, MIDI- or PCM-data streams which represent the same polyphonic piano piece.
    • Chord Segmentation and Recognition using EM-Trained Hidden Markov Models 

      Alexander Sheh; Daniel P.W. Ellis (Johns Hopkins University, 2003-10-26)
      Automatic extraction of content description from commercial audio recordings has a number of important applications, from indexing and retrieval through to novel musicological analyses based on very large corpora of recorded ...
    • Classification of Dance Music by Periodicity Patterns 

      Simon Dixon; Elias Pampalk; Gerhard Widmer (Johns Hopkins University, 2003-10-26)
      This paper addresses the genre classification problem for a specific subset of music, standard and Latin ballroom dance music, using a classification method based only on timing information. We compare two methods of ...
    • Features for audio and music classification 

      Martin McKinney; Jeroen Breebaart (Johns Hopkins University, 2003-10-26)
      Four audio feature sets are evaluated in their ability to classify five general audio classes and seven popular music genres. The feature sets include low-level signal properties, mel-frequency spectral coefficients, and ...
    • 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 ...