Now showing items 1-19 of 19

    • 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 Mood Detection from Acoustic Music Data 

      Dan Liu; Lie Lu; Hong-Jiang Zhang (Johns Hopkins University, 2003-10-26)
      Music mood describes the inherent emotional meaning of a music clip. It is helpful in music understanding and music search and some music-related applications. In this paper, a hierarchical framework is presented to automate ...
    • Automatic Music Transcription from Multiphonic MIDI Signals 

      Haruto Takeda; Takuya Nishimoto; Shigeki Sagayama (Johns Hopkins University, 2003-10-26)
      For automatically transcribing human-performed polyphonic music recorded in the MIDI format, rhythm and tempo are decomposed through probabilistic modeling using Viterbi search in HMM for recognizing the rhythm and EM ...
    • 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 ...
    • Determining Context-Defining Windows: Pitch Spelling using the Spiral Array 

      Elaine Chew; Yun-Ching Chen (Johns Hopkins University, 2003-10-26)
      This paper presents algorithms for pitch spelling using the Spiral Array model. Accurate pitch selling, assigning contextually consistent letter names to pitch numbers (for example, MIDI), is a critical component of music ...
    • Discovering Musical Pattern through Perceptive Heuristics. 

      Olivier Lartillot (Johns Hopkins University, 2003-10-26)
      This paper defends the view that the intricate difficulties challenging the emerging domain of Musical Pattern Discovery, which is dedicated to the automation of motivic analysis, will be overcome only through a thorough ...
    • 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 ...
    • 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 ...
    • 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. ...
    • 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 ...
    • Three Dimensional Continuous DP Algorithm for Multiple Pitch Candidates in Music Information Retrieval System 

      Sungphil Heo; Motoyuki Suzuki; Akinori Ito; Shozo Makino (Johns Hopkins University, 2003-10-26)
      This paper threats theoretical and practical issues that implement a music information retrieval system based on query by humming. In order to extract accuracy features from the user's humming, we propose a new retrieval ...
    • Using morphological description for generic sound retrieval 

      Julien Ricard; Perfecto Herrera (Johns Hopkins University, 2003-10-26)
      Systems for sound retrieval are usually “source-centred”. This means that retrieval is based on using the proper keywords that define or specify a sound source. Although this type of description is of great interest, it ...
    • Using Transportation Distances for Measuring Melodic Similarity 

      Rainer Typke; Panos Giannopoulos; Remco C. Veltkamp; Frans Wiering; René van Oostrum (Johns Hopkins University, 2003-10-26)
      Most of the existing methods for measuring melodic similarity use one-dimensional textual representations of music notation, so that melodic similarity can be measured by calculating editing distances. We view notes as ...