Title:

Melody Transcription From Music Audio: Approaches and Evaluation

Author(s):

Poliner, Graham E.
Ellis, Daniel P. W.
Ehmann, Andreas F.
Gomez, Emilia
Streich, Sebastian
Ong, Beesuan

Date:

2007

Type:

Articles

Department:

Electrical Engineering

Volume:

15

Permanent URL:

http://hdl.handle.net/10022/AC:P:12537

Book/Journal Title:

IEEE Transactions on Audio, Speech, and Language Processing

Abstract:

Although the process of analyzing an audio recording of a music performance is complex and difficult even for a human listener, there are limited forms of information that may be tractably extracted and yet still enable interesting applications. We discuss melody--roughly, the part a listener might whistle or hum--as one such reduced descriptor of music audio, and consider how to define it, and what use it might be. We go on to describe the results of full-scale evaluations of melody transcription systems conducted in 2004 and 2005, including an overview of the systems submitted, details of how the evaluations were conducted, and a discussion of the results. For our definition of melody, current systems can achieve around 70% correct transcription at the frame level, including distinguishing between the presence or absence of the melody. Melodies transcribed at this level are readily recognizable, and show promise for practical applications.

Subject(s):

Artificial intelligence
Music

DOI:

http://dx.doi.org/10.1109/TASL.2006.889797

Item views:

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Metadata:

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