Evaluation of AI Reverberation on Guitar

Manni CHEN; PerMagnus LINDBORG

Evaluation of AI Reverberation on Guitar

Manni CHEN^*, PerMagnus LINDBORG

^*Corresponding author for this work

School of Creative Media

Research output: Conference Papers › RGC 32 - Refereed conference paper (without host publication) › peer-review

Abstract

Artificial intelligence (AI) technology has been applied to create a range of different sound effects. However, perceptual evaluations of such applications have not yet been fully explored in research studies. This paper focuses on reverberation and we report results from objective measurements and perceptual listening tests in two stages (N=10, N=32). Participants rated samples of solo guitar phrases, taken from a musical context, and processed by either an AI software or by a professional sound engineer. The analysis aims to predict the salient modifications made to reverberation by AI and humans. This study contributes to our understanding of AI in studio music production. Future work will expand to other audio effects, such as compression and equalization.

Original language	English
Publication status	Published - Jul 2021
Event	16th International Conference on Music Perception and Cognition and 11th Triennial Conference of European Society for the Cognitive Sciences of Music (ICMPC16-ESCOM11): Connectivity and diversity in music cognition - Virtual Duration: 28 Jul 2021 → 31 Jul 2021 https://icmpc2021.sites.sheffield.ac.uk/home

Conference

Conference	16th International Conference on Music Perception and Cognition and 11th Triennial Conference of European Society for the Cognitive Sciences of Music (ICMPC16-ESCOM11)
Period	28/07/21 → 31/07/21
Internet address	https://icmpc2021.sites.sheffield.ac.uk/home

Research Keywords

reverberation
artificial intelligence
evaluation

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title = "Evaluation of AI Reverberation on Guitar",

abstract = "Artificial intelligence (AI) technology has been applied to create a range of different sound effects. However, perceptual evaluations of such applications have not yet been fully explored in research studies. This paper focuses on reverberation and we report results from objective measurements and perceptual listening tests in two stages (N=10, N=32). Participants rated samples of solo guitar phrases, taken from a musical context, and processed by either an AI software or by a professional sound engineer. The analysis aims to predict the salient modifications made to reverberation by AI and humans. This study contributes to our understanding of AI in studio music production. Future work will expand to other audio effects, such as compression and equalization.",

keywords = "reverberation, artificial intelligence, evaluation",

author = "Manni CHEN and PerMagnus LINDBORG",

year = "2021",

month = jul,

language = "English",

note = "16th International Conference on Music Perception and Cognition and 11th Triennial Conference of European Society for the Cognitive Sciences of Music (ICMPC16-ESCOM11) : Connectivity and diversity in music cognition ; Conference date: 28-07-2021 Through 31-07-2021",

url = "https://icmpc2021.sites.sheffield.ac.uk/home",

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Evaluation of AI Reverberation on Guitar. / CHEN, Manni ; LINDBORG, PerMagnus.
2021. Paper presented at 16th International Conference on Music Perception and Cognition and 11th Triennial Conference of European Society for the Cognitive Sciences of Music (ICMPC16-ESCOM11).

Research output: Conference Papers › RGC 32 - Refereed conference paper (without host publication) › peer-review

TY - CONF

T1 - Evaluation of AI Reverberation on Guitar

AU - CHEN, Manni

AU - LINDBORG, PerMagnus

PY - 2021/7

Y1 - 2021/7

N2 - Artificial intelligence (AI) technology has been applied to create a range of different sound effects. However, perceptual evaluations of such applications have not yet been fully explored in research studies. This paper focuses on reverberation and we report results from objective measurements and perceptual listening tests in two stages (N=10, N=32). Participants rated samples of solo guitar phrases, taken from a musical context, and processed by either an AI software or by a professional sound engineer. The analysis aims to predict the salient modifications made to reverberation by AI and humans. This study contributes to our understanding of AI in studio music production. Future work will expand to other audio effects, such as compression and equalization.

AB - Artificial intelligence (AI) technology has been applied to create a range of different sound effects. However, perceptual evaluations of such applications have not yet been fully explored in research studies. This paper focuses on reverberation and we report results from objective measurements and perceptual listening tests in two stages (N=10, N=32). Participants rated samples of solo guitar phrases, taken from a musical context, and processed by either an AI software or by a professional sound engineer. The analysis aims to predict the salient modifications made to reverberation by AI and humans. This study contributes to our understanding of AI in studio music production. Future work will expand to other audio effects, such as compression and equalization.

KW - reverberation

KW - artificial intelligence

KW - evaluation

UR - https://drive.google.com/file/d/1vLu89G6A9T79YrQE1gsH7uLeJxuNoEoZ/view

UR - https://drive.google.com/file/d/1yQ4g0mySttEvkHvuM1CIQTd0l2iMnsCI/view

UR - https://sites.google.com/sheffield.ac.uk/escom2021/program-abstract-and-video

M3 - RGC 32 - Refereed conference paper (without host publication)

T2 - 16th International Conference on Music Perception and Cognition and 11th Triennial Conference of European Society for the Cognitive Sciences of Music (ICMPC16-ESCOM11)

Y2 - 28 July 2021 through 31 July 2021

ER -

Evaluation of AI Reverberation on Guitar

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