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Grant: Discovery Grants Program - Individual

University of Regina

$17,000.00

Voice modeling for music information retrieval and human-computer interaction

EF 2008-09

Résumé
The human voice is an expressive and eloquent musical instrument. Song and other human-instrument music is ubiquitous in many cultures and is one of the primary forms of modern entertainment. With the rise of internet music sharing and sales, interacting with music is becoming a large research topic, but current techniques often concentrate on timbre, rhythm, and other characteristics that music listeners would consider the "background" of the music. Much of the "content" of current popular music is contained in the singer's lyrics, expression and style. When pitch is addressed, it is usually instrumental pitch, and when lyrics are considered, they are usually available as text. One of the primary goals of the music information retrieval community is to develop systems whereby a user can hum a tune and the system will identify that tune from a database of possible music. This difficult task is compounded when users want to add more information by singing lyrics. One of the aims of this work will be to develop feature models, signal processing techniques, and classification systems that allow for the transcription of human singing. People don't only listen to music, they create it as well. Many people claim that they cannot carry a tune, and yet are capable of humming or whistling along with the radio. This research has the potential to provide amateurs, untrained singers and even non-singers with the tools to interact with music in new and less threatening ways, and gain confidence with music. Professional singers will be provided with tools that make use of their training to facilitate writing of music, to hone their skill, and to interact with music in challenging and intriguing ways. In the long term, deep and accurate models of human song may lead to a computer that sings to us.
Programme
Discovery Grants Program - Individual
Bénéficiaire
Emplacement
Saskatchewan, Canada
Type de bénéficiaire
Academia
Type
Grant
Source
NSERC's Awards Data

Tel que publié

Application id
288337-2007
Name nom
Gerhard, David
Department département
Computer Science
Organization id
17
Institution établissement
University of Regina
Province en
Saskatchewan
Province fr
Saskatchewan
Country en
CANADA
Country fr
CANADA
Fiscal year exercice financier
2008
Competition year année de concours
2007
Award amount
17000
Program id
RGPIN
Program nane en
Discovery Grants Program - Individual
Program name fr
Programme de subventions à la découverte - individuelles
Group en
Discovery grants programs
Group fr
Programmes de subventions à la découverte
Committee code
331
Committee name en
Computing and Information Sciences - B
Committee name fr
Informatique - B
Area of application code
1207
Area of application group en
Advancement of knowledge
Area of application group fr
Avancement des connaissances
Area of application en
Information, computer and communication technologies
Area of application fr
Technologie de l'information, des ordinateurs et des réseaux de communications
Research subject code
2721
Research subject group en
Information technology
Research subject group fr
Technologie de l'information
Research subject en
Multimedia systems and networks
Research subject fr
Systèmes et réseaux multimédias
Partie
2
Nb partie
5
Application title
Voice modeling for music information retrieval and human-computer interaction
Keyword
NA
Application summary
The human voice is an expressive and eloquent musical instrument. Song and other human-instrument music is ubiquitous in many cultures and is one of the primary forms of modern entertainment. With the rise of internet music sharing and sales, interacting with music is becoming a large research topic, but current techniques often concentrate on timbre, rhythm, and other characteristics that music listeners would consider the "background" of the music. Much of the "content" of current popular music is contained in the singer's lyrics, expression and style. When pitch is addressed, it is usually instrumental pitch, and when lyrics are considered, they are usually available as text. One of the primary goals of the music information retrieval community is to develop systems whereby a user can hum a tune and the system will identify that tune from a database of possible music. This difficult task is compounded when users want to add more information by singing lyrics. One of the aims of this work will be to develop feature models, signal processing techniques, and classification systems that allow for the transcription of human singing. People don't only listen to music, they create it as well. Many people claim that they cannot carry a tune, and yet are capable of humming or whistling along with the radio. This research has the potential to provide amateurs, untrained singers and even non-singers with the tools to interact with music in new and less threatening ways, and gain confidence with music. Professional singers will be provided with tools that make use of their training to facilitate writing of music, to hone their skill, and to interact with music in challenging and intriguing ways. In the long term, deep and accurate models of human song may lead to a computer that sings to us.