Cargando…

Modeling Noise-Related Timbre Semantic Categories of Orchestral Instrument Sounds With Audio Features, Pitch Register, and Instrument Family

Audio features such as inharmonicity, noisiness, and spectral roll-off have been identified as correlates of “noisy” sounds. However, such features are likely involved in the experience of multiple semantic timbre categories of varied meaning and valence. This paper examines the relationships of sti...

Descripción completa

Detalles Bibliográficos
Autores principales: Reymore, Lindsey, Beauvais-Lacasse, Emmanuelle, Smith, Bennett K., McAdams, Stephen
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9010607/
https://www.ncbi.nlm.nih.gov/pubmed/35432090
http://dx.doi.org/10.3389/fpsyg.2022.796422
_version_ 1784687515675918336
author Reymore, Lindsey
Beauvais-Lacasse, Emmanuelle
Smith, Bennett K.
McAdams, Stephen
author_facet Reymore, Lindsey
Beauvais-Lacasse, Emmanuelle
Smith, Bennett K.
McAdams, Stephen
author_sort Reymore, Lindsey
collection PubMed
description Audio features such as inharmonicity, noisiness, and spectral roll-off have been identified as correlates of “noisy” sounds. However, such features are likely involved in the experience of multiple semantic timbre categories of varied meaning and valence. This paper examines the relationships of stimulus properties and audio features with the semantic timbre categories raspy/grainy/rough, harsh/noisy, and airy/breathy. Participants (n = 153) rated a random subset of 52 stimuli from a set of 156 approximately 2-s orchestral instrument sounds representing varied instrument families (woodwinds, brass, strings, percussion), registers (octaves 2 through 6, where middle C is in octave 4), and both traditional and extended playing techniques (e.g., flutter-tonguing, bowing at the bridge). Stimuli were rated on the three semantic categories of interest, as well as on perceived playing exertion and emotional valence. Correlational analyses demonstrated a strong negative relationship between positive valence and perceived physical exertion. Exploratory linear mixed models revealed significant effects of extended technique and pitch register on valence, the perception of physical exertion, raspy/grainy/rough, and harsh/noisy. Instrument family was significantly related to ratings of airy/breathy. With an updated version of the Timbre Toolbox (R-2021 A), we used 44 summary audio features, extracted from the stimuli using spectral and harmonic representations, as input for various models built to predict mean semantic ratings for each sound on the three semantic categories, on perceived exertion, and on valence. Random Forest models predicting semantic ratings from audio features outperformed Partial Least-Squares Regression models, consistent with previous results suggesting that non-linear methods are advantageous in timbre semantic predictions using audio features. Relative Variable Importance measures from the models among the three semantic categories demonstrate that although these related semantic categories are associated in part with overlapping features, they can be differentiated through individual patterns of audio feature relationships.
format Online
Article
Text
id pubmed-9010607
institution National Center for Biotechnology Information
language English
publishDate 2022
publisher Frontiers Media S.A.
record_format MEDLINE/PubMed
spelling pubmed-90106072022-04-16 Modeling Noise-Related Timbre Semantic Categories of Orchestral Instrument Sounds With Audio Features, Pitch Register, and Instrument Family Reymore, Lindsey Beauvais-Lacasse, Emmanuelle Smith, Bennett K. McAdams, Stephen Front Psychol Psychology Audio features such as inharmonicity, noisiness, and spectral roll-off have been identified as correlates of “noisy” sounds. However, such features are likely involved in the experience of multiple semantic timbre categories of varied meaning and valence. This paper examines the relationships of stimulus properties and audio features with the semantic timbre categories raspy/grainy/rough, harsh/noisy, and airy/breathy. Participants (n = 153) rated a random subset of 52 stimuli from a set of 156 approximately 2-s orchestral instrument sounds representing varied instrument families (woodwinds, brass, strings, percussion), registers (octaves 2 through 6, where middle C is in octave 4), and both traditional and extended playing techniques (e.g., flutter-tonguing, bowing at the bridge). Stimuli were rated on the three semantic categories of interest, as well as on perceived playing exertion and emotional valence. Correlational analyses demonstrated a strong negative relationship between positive valence and perceived physical exertion. Exploratory linear mixed models revealed significant effects of extended technique and pitch register on valence, the perception of physical exertion, raspy/grainy/rough, and harsh/noisy. Instrument family was significantly related to ratings of airy/breathy. With an updated version of the Timbre Toolbox (R-2021 A), we used 44 summary audio features, extracted from the stimuli using spectral and harmonic representations, as input for various models built to predict mean semantic ratings for each sound on the three semantic categories, on perceived exertion, and on valence. Random Forest models predicting semantic ratings from audio features outperformed Partial Least-Squares Regression models, consistent with previous results suggesting that non-linear methods are advantageous in timbre semantic predictions using audio features. Relative Variable Importance measures from the models among the three semantic categories demonstrate that although these related semantic categories are associated in part with overlapping features, they can be differentiated through individual patterns of audio feature relationships. Frontiers Media S.A. 2022-04-01 /pmc/articles/PMC9010607/ /pubmed/35432090 http://dx.doi.org/10.3389/fpsyg.2022.796422 Text en Copyright © 2022 Reymore, Beauvais-Lacasse, Smith and McAdams. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Psychology
Reymore, Lindsey
Beauvais-Lacasse, Emmanuelle
Smith, Bennett K.
McAdams, Stephen
Modeling Noise-Related Timbre Semantic Categories of Orchestral Instrument Sounds With Audio Features, Pitch Register, and Instrument Family
title Modeling Noise-Related Timbre Semantic Categories of Orchestral Instrument Sounds With Audio Features, Pitch Register, and Instrument Family
title_full Modeling Noise-Related Timbre Semantic Categories of Orchestral Instrument Sounds With Audio Features, Pitch Register, and Instrument Family
title_fullStr Modeling Noise-Related Timbre Semantic Categories of Orchestral Instrument Sounds With Audio Features, Pitch Register, and Instrument Family
title_full_unstemmed Modeling Noise-Related Timbre Semantic Categories of Orchestral Instrument Sounds With Audio Features, Pitch Register, and Instrument Family
title_short Modeling Noise-Related Timbre Semantic Categories of Orchestral Instrument Sounds With Audio Features, Pitch Register, and Instrument Family
title_sort modeling noise-related timbre semantic categories of orchestral instrument sounds with audio features, pitch register, and instrument family
topic Psychology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9010607/
https://www.ncbi.nlm.nih.gov/pubmed/35432090
http://dx.doi.org/10.3389/fpsyg.2022.796422
work_keys_str_mv AT reymorelindsey modelingnoiserelatedtimbresemanticcategoriesoforchestralinstrumentsoundswithaudiofeaturespitchregisterandinstrumentfamily
AT beauvaislacasseemmanuelle modelingnoiserelatedtimbresemanticcategoriesoforchestralinstrumentsoundswithaudiofeaturespitchregisterandinstrumentfamily
AT smithbennettk modelingnoiserelatedtimbresemanticcategoriesoforchestralinstrumentsoundswithaudiofeaturespitchregisterandinstrumentfamily
AT mcadamsstephen modelingnoiserelatedtimbresemanticcategoriesoforchestralinstrumentsoundswithaudiofeaturespitchregisterandinstrumentfamily