Publication

A new time-frequency representation for music signal analysis: Resonator Time-Frequency Image

Marco Mattavelli
2007
Conference Papers

Abstract

Most of music related tasks need a joint time-because a music signal varies with time. The existing time-frequency analysis approaches show some serious limitations for application in music signal processing. This paper presents an original frequency-dependent time-frequency analysis tool called the Resonator Time-Frequency Image (RTFI). The RTFI is implemented by a first-order complex resonator bank so as to be computation-efficient. Different music analysis tasks may have different time-frequency resolution requirements. Using the RTFI, one can select different time-frequency resolutions, such as uniform analysis, constant-Q analysis, or ear-like analysis by simply setting different parameters; and letting the RTFI generalize all these analyses in one framework. An example of using the RTFI in music onset detection is introduced.

Official source

https://infoscience.epfl.ch/entities/publication/c807cefc-d1e0-45ca-8829-4b9d4c7a438a

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Marco Mattavelli
2007
Conference Papers

Abstract

Official source

https://infoscience.epfl.ch/entities/publication/c807cefc-d1e0-45ca-8829-4b9d4c7a438a

About this result

Related concepts (32)

Time–frequency analysis

In signal processing, time–frequency analysis comprises those techniques that study a signal in both the time and frequency domains simultaneously, using various time–frequency representations. Rather than viewing a 1-dimensional signal (a function, real or complex-valued, whose domain is the real line) and some transform (another function whose domain is the real line, obtained from the original via some transform), time–frequency analysis studies a two-dimensional signal – a function whose domain is the two-dimensional real plane, obtained from the signal via a time–frequency transform.

Neuroscience of music

The neuroscience of music is the scientific study of brain-based mechanisms involved in the cognitive processes underlying music. These behaviours include music listening, performing, composing, reading, writing, and ancillary activities. It also is increasingly concerned with the brain basis for musical aesthetics and musical emotion. Scientists working in this field may have training in cognitive neuroscience, neurology, neuroanatomy, psychology, music theory, computer science, and other relevant fields.

Music information retrieval

Music information retrieval (MIR) is the interdisciplinary science of retrieving information from music. Those involved in MIR may have a background in academic musicology, psychoacoustics, psychology, signal processing, informatics, machine learning, optical music recognition, computational intelligence or some combination of these. MIR is being used by businesses and academics to categorize, manipulate and even create music.

Related publications (2)

A new time-frequency representation for music signal analysis: Resonator Time-Frequency Image

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