Now showing items 3-12 of 12

    • The dangers of parsimony in query-by-humming applications 

      Colin Meek; William Birmingham (Johns Hopkins University, 2003-10-26)
      Query-by-humming systems attempt to address the needs of the non-expert user, for whom the most natural query format -- for the purposes of finding a tune, hook or melody of unknown providence -- is to sing it. While human ...
    • Design Patterns in XML Music Representation 

      Perry Roland (Johns Hopkins University, 2003-10-26)
      Design patterns attempt to formalize the discussion of recurring problems and their solutions. This paper introduces several XML design patterns and demonstrates their usefulness in the development of XML music representations. ...
    • Detecting Emotion in Music 

      Tao Li; Mitsunori Ogihara (Johns Hopkins University, 2003-10-26)
      Detection of emotion in music sounds is an important problem in music indexing. This paper studies the problem of identifying emotion in music by sound signal processing. The problem is cast as a multiclass classification ...
    • 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 ...
    • 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 ...
    • 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. ...
    • A scalable Peer-to-Peer System for Music Content and Information Retrieval 

      George Tzanetakis; Jun Gao; Peter Steenkiste (Johns Hopkins University, 2003-10-26)
      Currently a large percentage of internet traffice consists of music files, typically stored in MP3 compressed audio format, shared and exchanged over Peer-to-Peer (P2P) networks. Searching for music is performed by specifying ...
    • A Specialized Open Archives Initiative Harvester for Sheet Music: A Project Report and Examination of Issues 

      Stephen Davison; Cynthia Requardt; Kristine Brancolini (Johns Hopkins University, 2003-10-26)
      The Open Archives Initiative (OAI) Sheet Music Project is a consortium of institutions building OAI-compliant data providers, a metadata harvester, and a web-based service provider for digital sheet music collections. The ...
    • Toward the Scientific Evaluation of Music Information Retrieval Systems 

      J. Stephen Downie (Johns Hopkins University, 2003-10-26)
      This paper outlines the findings-to-date of a project to assist in the efforts being made to establish a TREC-like evaluation paradigm within the Music Information Retrieval (MIR) research community. The findings and ...