An unsupervised approach to the semantic description of the sound quality of violins

Buccoli, Michele; Zanoni, Massimiliano; Setragno, Francesco; Antonacci, Fabio; Sarti, Augusto

doi:10.1109/eusipco.2015.7362735

Cited by 5 publications

(4 citation statements)

References 11 publications

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“…The next step for this system is polyphonic music transcription. Also, this system can be extended in the field of musical instrument recognition [18,10] and the detection of different playing techniques on different instruments. For example, tapping, vibrato [4], staccato, etc.…”

Section: Discussionmentioning

confidence: 99%

MOMOS-MT: mobile monophonic system for music transcription

Makhmutov

Brown

Mazzara

et al. 2017

Proceedings of the Symposium on Applied Computing

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Music holds a significant cultural role in social identity and in the encouragement of socialization. Technology, by the destruction of physical and cultural distance, has lead to many changes in musical themes and the complete loss of forms. Yet, it also allows for the preservation and distribution of music from societies without a history of written sheet music. This paper presents early work on a tool for musicians and ethnomusicologists to transcribe sheet music from monophonic voiced pieces for preservation and distribution. Using FFT, the system detects the pitch frequencies, also other methods detect note durations tempo, time signatures and generates sheet music. The final system is able to be used in mobile platforms allowing the user to take recordings and produce sheet music in situ to a performance.

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Section: Discussionmentioning

confidence: 99%

MOMOS-MT: mobile monophonic system for music transcription

Makhmutov

Brown

Mazzara

et al. 2017

Proceedings of the Symposium on Applied Computing

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“…A semantic description of the violin timbre was also provided in [35] and [36], where a set of bipolar descriptors from natural language are modeled by means of large sets of acoustic cues extracted by 28 historical and modern violins.…”

Section: Feature-based Timbral Analysismentioning

confidence: 99%

Feature-Based Analysis of the Impact of Ground Coat and Varnish on Violin Tone Qualities

Setragno¹,

Zanoni²,

Antonacci³

et al. 2017

Acta Acustica united with Acustica

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Assessing the tonal qualities of an acoustic musical instrument is a challenge that has long been pursued by researchers in musical acoustics. This is a topic of particular interest when it comes to discussing the case of violins. Historical violins are often believed to owe a great deal of their celebrated timbral qualities to the choice and the make of their finishings, particularly the ground coat and the varnish. The impact of such finishings on the instrument's tonal qualities, however, is not so well understood. In this paper we investigate the impact of the finishing process on the instrument's timbre through a joint analysis of the characteristics of the materials involved for this process (ground coat and varnish) and audio features extracted from the sound produced by such violins at various stages of their finishing. Some of the results are compared with those found in the literature for validation purposes. The characterization of the impact of ground coat and varnish has been conducted during the finishing process of a new violin.

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“…"I would like to compose a sad and rough piece, " is an example. The layered structure of deep learning methods resulted to be effective in modeling music at different levels of abstraction [19][20][21]. For this reason, much attention is focused today on the conditional music generation task, that is, varying the generated music according to some high-level parameter, which can be easily understood by a musician.…”

Section: Introductionmentioning

confidence: 99%

Variational Autoencoders for chord sequence generation conditioned on Western harmonic music complexity

Comanducci

Gioiosa

Zanoni

et al. 2023

J AUDIO SPEECH MUSIC PROC.

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In recent years, the adoption of deep learning techniques has allowed to obtain major breakthroughs in the automatic music generation research field, sparking a renewed interest in generative music. A great deal of work has focused on the possibility of conditioning the generation process in order to be able to create music according to human-understandable parameters. In this paper, we propose a technique for generating chord progressions conditioned on harmonic complexity, as grounded in the Western music theory. More specifically, we consider a pre-existing dataset annotated with the related complexity values and we train two variations of Variational Autoencoders (VAE), namely a Conditional-VAE (CVAE) and a Regressor-based VAE (RVAE), in order to condition the latent space depending on the complexity. Through a listening test, we analyze the effectiveness of the proposed techniques.

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An unsupervised approach to the semantic description of the sound quality of violins

Cited by 5 publications

References 11 publications

MOMOS-MT: mobile monophonic system for music transcription

MOMOS-MT: mobile monophonic system for music transcription

Feature-Based Analysis of the Impact of Ground Coat and Varnish on Violin Tone Qualities

Variational Autoencoders for chord sequence generation conditioned on Western harmonic music complexity

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