Corpus ID: 67926553

An Investigation into the Use of Artificial Intelligence Techniques for the Analysis and Control of Instrumental Timbre and Timbral Combinations

@inproceedings{Antoine2018AnII,
  title={An Investigation into the Use of Artificial Intelligence Techniques for the Analysis and Control of Instrumental Timbre and Timbral Combinations},
  author={Aur{\'e}lien Antoine},
  year={2018}
}
Researchers have investigated harnessing computers as a tool to aid in the composition of music for over 70 years. In major part, such research has focused on creating algorithms to work with pitches and rhythm, which has resulted in a selection of sophisticated systems. Although the musical possibilities of these systems are vast, they are not directly considering another important characteristic of sound. Timbre can be defined as all the sound attributes, except pitch, loudness and duration… Expand

References

SHOWING 1-10 OF 263 REFERENCES
Predicting timbral and perceptual characteristics of orchestral instrument combinations
TLDR
Using supervised learning methods to create regression and classification models, it is possible to predict specific timbral and perceptual characteristics from information about a combination of different orchestral instruments, which would provide methods to estimate the perception of instrument timbre fusions directly from abstract information. Expand
Timbre as a structuring force in music
TLDR
This work seeks to develop a theoretical ground for orchestration practice starting with the structuring role that timbre can play in music, and examines how such principles might be incorporated into computer-aided orchestration systems and computer- aided orchestral rendering systems. Expand
Timbre Space as a Musical Control Structure
TLDR
A system for taking subjective measures of perceptual contrast between sound objects and using this data as input to some computer programs for additive synthesis and allow for the manipulation of the evolving spectral energy distribution and various temporal features of the tones. Expand
Exploration of timbre by analysis and synthesis
Publisher Summary This chapter explains the exploration of timbre by analysis and synthesis. Timber is referred as the quality of sound. It is the perceptual attribute that helps in distinguishingExpand
Musical Timbre Perception
Musical timbre encompasses a complex set of auditory attributes and raises a plethora of musical and psychological issues. To discover the underlying perceptual structure of timbre, psychophysicalExpand
Perspectives on the Contribution of Timbre to Musical Structure
  • S. McAdams
  • Computer Science
  • Computer Music Journal
  • 1999
TLDR
An overview of some (but not all) of the work on timbre performed by the Music Perception and Cognition team at IRCAM is presented, and the role of timbre in the creation and perceptual organization of musical materials is addressed. Expand
Perceptually Salient Regions of the Modulation Power Spectrum for Musical Instrument Identification
TLDR
The results suggest that musical instrument timbres are characterized by specific spectrotemporal modulations, information which could contribute to music information retrieval tasks such as automatic source recognition. Expand
Music in Our Ears: The Biological Bases of Musical Timbre Perception
TLDR
The study demonstrates that joint spectro-temporal features, such as those observed in the mammalian primary auditory cortex, are critical to provide the rich-enough representation necessary to account for perceptual judgments of timbre by human listeners, as well as recognition of musical instruments. Expand
A perceptually orientated approach for automatic classification of timbre content of orchestral excerpts
In this paper, we report on the development of a perceptually orientated and automatic classification system of timbre content within orchestral audio samples. Here, we have decided to investigateExpand
Comparison of features for musical instrument recognition
  • A. Eronen
  • Engineering
  • Proceedings of the 2001 IEEE Workshop on the Applications of Signal Processing to Audio and Acoustics (Cat. No.01TH8575)
  • 2001
Several features were compared with regard to recognition performance in a musical instrument recognition system. Both mel-frequency and linear prediction cepstral and delta cepstral coefficientsExpand
...
1
2
3
4
5
...