Mid-level Representations of Musical Audio Signals for Music Information Retrieval

Kitahara, Tetsuro

doi:10.1007/978-3-642-11674-2_4

Cited by 4 publications

(3 citation statements)

References 23 publications

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“…To summarize the audio features, the combination of low-level and mid-level features would give better results in music processing tasks [56]. Timbre and spectral features are suitable for genre and instrument classification.…”

Section: Overview Of Mid-level Featuresmentioning

confidence: 99%

A Review: Music Feature Extraction from an Audio Signal

Jitendra¹

2020

IJATCSE

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In recent years, the revenue earned through digital music stood at a billion-dollar market and the US remained the most profitable market for Digital music. Due to the digital shift, today people have access to millions of music clips from online music applications through their smart phones. In this context, there are some issues identified between the music listeners, music search engine by querying and retrieving music clips from a large collection of music data set. Classification is one of the fundamental problems in music information retrieval (MIR). Still, there are some hurdles according to their listener's preferences regarding music collections and their categorization. In this paper, different music extraction features are addressed, which can be used in various tasks related to music classification like a listener's mood, instrument recognition, artist identification, genre, query-by-humming, and music annotation. This review illustrates various features that can be used for addressing the research challenges posed by music mining.

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Section: Overview Of Mid-level Featuresmentioning

confidence: 99%

A Review: Music Feature Extraction from an Audio Signal

Jitendra¹

2020

IJATCSE

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“…From then on, several music players began incorporating visualiser software and the concept became widespread. In this time it became common to use low-level audio features, such as spectral features to produce abstract imagery [20]. Possibly the earliest visualiser using this approach was Cthugha, initially released in 1993 [21].…”

Section: Background and Related Workmentioning

confidence: 99%

Towards Music-Driven Procedural Animation

Brito

Fernandes

2019

2019 International Conference on Graphics and Interaction (ICGI)

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“…With the invention of computers and the beginning of the digital era, the elaboration of sound signals highlighted the need for more abstract information characterizing audio recordings. Thus, researchers started proposing mid-level representations [5], with reference to symbolic and physical levels [6]. Nowadays, the availability of vast, easily accessible quantities of data, along with appropriate modern computational technologies, encourages the collection of various types of meta-data, which can be either cultural or editorial [7].…”

Section: Introductionmentioning

confidence: 99%

Multimodal Music Information Processing and Retrieval: Survey and Future Challenges

Simonetta

Ntalampiras

Avanzini

2019

2019 International Workshop on Multilayer Music Representation and Processing (MMRP)

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Towards improving the performance in various music information processing tasks, recent studies exploit different modalities able to capture diverse aspects of music. Such modalities include audio recordings, symbolic music scores, midlevel representations, motion and gestural data, video recordings, editorial or cultural tags, lyrics and album cover arts. This paper critically reviews the various approaches adopted in Music Information Processing and Retrieval, and highlights how multimodal algorithms can help Music Computing applications. First, we categorize the related literature based on the application they address. Subsequently, we analyze existing information fusion approaches, and we conclude with the set of challenges that Music Information Retrieval and Sound and Music Computing research communities should focus in the next years.

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Mid-level Representations of Musical Audio Signals for Music Information Retrieval

Cited by 4 publications

References 23 publications

A Review: Music Feature Extraction from an Audio Signal

A Review: Music Feature Extraction from an Audio Signal

Towards Music-Driven Procedural Animation

Multimodal Music Information Processing and Retrieval: Survey and Future Challenges

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