Now showing items 18-37 of 48

    • Effectiveness of HMM-Based Retrieval on Large Databases 

      Jonah Shifrin; William Birmingham (Johns Hopkins University, 2003-10-26)
      We have investigated the performance of a hidden Markov model based QBH retrieval system on a large musical database. The database is synthetic, generated from statistics gleaned from our (smaller) database of musical ...
    • Effects of song familiarity, singing training and recent song exposure on the singing of melodies 

      Steffen Pauws (Johns Hopkins University, 2003-10-26)
      Findings of a singing experiment are presented in which trained and untrained singers sang melodies of familiar and less familiar Beatles songs from memory and after listening to the original song on CD. Results showed ...
    • Exploring Music Collections by Browsing Different Views 

      Elias Pampalk; Simon Dixon; Gerhard Widmer (Johns Hopkins University, 2003-10-26)
      The availability of large music collections calls for ways to efficiently access and explore them. We present a new approach which uses descriptors derived from audio analysis and meta-information to create different views ...
    • 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 ...
    • Geometric Algorithms for Transposition Invariant Content-Based Music Retrieval 

      Esko Ukkonen; Kjell Lemström; Veli Mäkinen (Johns Hopkins University, 2003-10-26)
      We represent music as sets of points or sets of horizontal line segments in the Euclidean plane. Via this geometric representation we cast transposition invariant content-based music retrieval problems as ones of matching ...
    • 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 ...
    • Harmonic Analysis with Probabilistic Graphical Models 

      Christopher Raphael; Josh Stoddard (Johns Hopkins University, 2003-10-26)
      A technique for harmonic analysis is presented that partitions a piece of music into contiguous regions and labels each with the key, mode, and functional chord, e.g. tonic, dominant, etc. The analysis is performed with a ...
    • 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 ...
    • How People Describe Their Music Information Needs: A Grounded Theory Analysis Of Music Queries 

      David Bainbridge; Sally Jo Cunningham; J. Stephen Downie (Johns Hopkins University, 2003-10-26)
      How do users of music information retrieval (MIR) systems express their needs? Using a Wizard of Oz approach to system evaluation, combined with a grounded theory analysis of 502 real-world music queries posted to Google ...
    • The Importance of Cross Database Evaluation in Sound Classification 

      Arie Livshin; Xavier Rodet (Johns Hopkins University, 2003-10-26)
      In numerous articles (Martin and Kim, 1998; Fraser and Fujinaga, 1999; and many others) sound classification algorithms are evaluated using "self classification" - the learning and test groups are randomly selected out of ...
    • Improving Polyphonic and Poly-Instrumental Music to Score Alignment 

      Ferréol Soulez; Xavier Rodet; Diemo Schwarz (Johns Hopkins University, 2003-10-26)
      Music alignment link events in a score and points on the audio performance time axis. All the parts of a recording can be thus indexed according to score information. The automatic alignment presented in this paper is based ...
    • Key-specific Shrinkage Techniques for Harmonic Models 

      Jeremy Pickens (Johns Hopkins University, 2003-10-26)
      Statistical modeling of music is rapidly gaining acceptance as viable approach to a host of Music Information Retrieval related tasks, from transcription to ad hoc retrieval. As music may be viewed as an evolving pattern ...
    • A Large-Scale Evaluation of Acoustic and Subjective Music Similarity Measures 

      Adam Berenzweig; Beth Logan; Daniel Ellis; Brian Whitman (Johns Hopkins University, 2003-10-26)
      Subjective similarity between musical pieces and artists is an elusive concept, but one that music be pursued in support of applications to provide automatic organization of large music collections. In this paper, we examine ...
    • 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 ...
    • The MUSART Testbed for Query-By-Humming Evaluation 

      Roger Dannenberg; William Birmingham; George Tzanetakis; Colin Meek; Ning Hu; Bryan Pardo (Johns Hopkins University, 2003-10-26)
      Evaluating music information retrieval systems is acknowledged to be a difficult problem. We have created a database and a software testbed for the systematic evaluation of various query-by-humming (QBH) search systems. ...
    • Music identification by Leadsheets 

      Frank Seifert; Wolfgang Benn (Johns Hopkins University, 2003-10-26)
      Most experimental research on content-based automatic recognition and identification of musical documents is founded on statistical distribution of timbre or simple retrieval mechanisms like comparison of melodic segments. ...
    • Music Notation as a MEI Feasibility Test 

      Baron Schwartz (Johns Hopkins University, 2003-10-26)
      This project demonstrated that enough information can be retrieved from MEI, an XML format for musical information representation, to transform it into music notation with good fidelity. The process involved writing an ...
    • Music Scene Description Project: Toward Audio-based Real-time Music Understanding 

      Masataka Goto (Johns Hopkins University, 2003-10-26)
      This paper reports a research project intended to build a real-time music-understanding system producing intuitively meaningful descriptions of real-world musical audio signals, such as the melody lines and chorus sections. ...
    • Position Indexing of Adjacent and Concurrent N-Grams for Polyphonic Music Retrieval 

      Shyamala Doraisamy; Stefan Rüger (Johns Hopkins University, 2003-10-26)
      In this paper we examine the retrieval performance of adjacent and concurrent n-grams generated from polyphonic music data. We deploy a method to index polyphonic music using a word position indexer with the n-gram approach. ...