Now showing items 1-20 of 48

    • 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 ...
    • 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 ...
    • 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 ...
    • 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 ...
    • 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 ...
    • 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 ...
    • 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 ...
    • 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 ...
    • 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 ...
    • RWC Music Database: Music Genre Database and Musical Instrument Sound Database 

      Masataka Goto; Hiroki Hashiguchi; Takuichi Nishimura; Ryuichi Oka (Johns Hopkins University, 2003-10-26)
      This paper describes the design policy and specifications of the RWC Music Database, a copyright-cleared music database (DB) compiled specifically for research purposes. Shared DBs are common in other research fields and ...
    • 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. ...
    • 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 ...
    • 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 ...
    • 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 ...
    • 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 ...
    • Chopin Early Editions: Construction and Usage of Online Digital Scores 

      Tod Olson; J. Stephen Downie (Johns Hopkins University, 2003-10-26)
      The University of Chicago Library has digitized a collection of 19th century music scores. The online collection is generated programmatically from the scanned images and human-created descriptive and structural metadata, ...
    • 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 ...
    • 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 ...