• Login
    Search 
    •   JScholarship Home
    • Library-Sponsored Conference Proceedings
    • Search
    •   JScholarship Home
    • Library-Sponsored Conference Proceedings
    • Search
    JavaScript is disabled for your browser. Some features of this site may not work without it.

    Search

    Show Advanced FiltersHide Advanced Filters

    Filters

    Use filters to refine the search results.

    Now showing items 1-10 of 26

    • Sort Options:
    • Relevance
    • Title Asc
    • Title Desc
    • Issue Date Asc
    • Issue Date Desc
    • Results Per Page:
    • 5
    • 10
    • 20
    • 40
    • 60
    • 80
    • 100
    Thumbnail

    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 ...
    Thumbnail

    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 ...
    Thumbnail

    Blind Clustering of Popular Music Recordings Based on Singer Voice Characteristics 

    Wei-Ho Tsai; Hsin-Min Wang; Dwight Rodgers; Shi-Sian Cheng; Hung-Min Yu (Johns Hopkins University, 2003-10-26)
    This paper presents an effective technique for automatically clustering undocumented music recordings based on their associated singer. This serves as an indispensable step towards indexing and content-based information ...
    Thumbnail

    The C-BRAHMS project 

    Kjell Lemström; Veli Mäkinen; Anna Pienimäki; Mika Turkia; Esko Ukkonen (Johns Hopkins University, 2003-10-26)
    The C-BRAHMS project develops computational methods for content-based retrieval and analysis of music data. A summary of the recent algorithmic and experimental developments of the project is given. A search engine developed ...
    Thumbnail

    Automatic Segmentation, Learning and Retrieval of Melodies Using A Self-Organizing Neural Network 

    Steven Harford (Johns Hopkins University, 2003-10-26)
    We introduce a neural network, known as SONNET-MAP, capable of automatic segmentation, learning and retrieval of melodies. SONNET-MAP is a synthesis of Nigrin’s SONNET (Self-Organizing Neural NETwork) architecture and an ...
    Thumbnail

    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. ...
    Thumbnail

    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 ...
    Thumbnail

    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 ...
    Thumbnail

    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. ...
    Thumbnail

    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 ...
    • 1
    • 2
    • 3

    DSpace software copyright © 2002-2016  DuraSpace
    Policies | Contact Us | Send Feedback
    Theme by 
    Atmire NV
     

     

    Browse

    All of JScholarshipCommunities & CollectionsBy Issue DateAuthorsTitlesSubjectsThis CommunityBy Issue DateAuthorsTitlesSubjects

    My Account

    LoginRegister

    Discover

    AuthorWilliam Birmingham (3)Colin Meek (2)Elias Pampalk (2)Esko Ukkonen (2)George Tzanetakis (2)Gerhard Widmer (2)Kjell Lemström (2)Simon Dixon (2)Veli Mäkinen (2)Akinori Ito (1)... View MoreSubject
    IR Systems and Algorithms (26)
    Digital Libraries (9)Music Analysis (6)Audio (5)Perception and Cognition (3)General Interest (2)... View MoreDate Issued2003 (26)Has File(s)Yes (26)

    DSpace software copyright © 2002-2016  DuraSpace
    Policies | Contact Us | Send Feedback
    Theme by 
    Atmire NV