Now showing items 1-20 of 26

    • An Auditory Model Based Transcriber of Vocal Queries 

      Tom De Mulder; Jean-Pierre Martens; Micheline Lesaffre; Marc Leman; Bernard De Baets; Hans De Meyer (Johns Hopkins University, 2003-10-26)
      In this paper a new auditory model-based transcriber of melodic queries produced by a human voice is presented. The newly presented system is tested systematically, together with some other state-of-the-art systems, on ...
    • 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 ...
    • 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.
    • 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 ...
    • 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 ...
    • 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 ...
    • 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 ...
    • 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 ...
    • 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 ...
    • 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 ...
    • 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 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. ...
    • 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. ...