Dataset Information

Modeling Timbre Similarity of Short Music Clips.

ABSTRACT: There is evidence from a number of recent studies that most listeners are able to extract information related to song identity, emotion, or genre from music excerpts with durations in the range of tenths of seconds. Because of these very short durations, timbre as a multifaceted auditory attribute appears as a plausible candidate for the type of features that listeners make use of when processing short music excerpts. However, the importance of timbre in listening tasks that involve short excerpts has not yet been demonstrated empirically. Hence, the goal of this study was to develop a method that allows to explore to what degree similarity judgments of short music clips can be modeled with low-level acoustic features related to timbre. We utilized the similarity data from two large samples of participants: Sample I was obtained via an online survey, used 16 clips of 400 ms length, and contained responses of 137,339 participants. Sample II was collected in a lab environment, used 16 clips of 800 ms length, and contained responses from 648 participants. Our model used two sets of audio features which included commonly used timbre descriptors and the well-known Mel-frequency cepstral coefficients as well as their temporal derivates. In order to predict pairwise similarities, the resulting distances between clips in terms of their audio features were used as predictor variables with partial least-squares regression. We found that a sparse selection of three to seven features from both descriptor sets-mainly encoding the coarse shape of the spectrum as well as spectrotemporal variability-best predicted similarities across the two sets of sounds. Notably, the inclusion of non-acoustic predictors of musical genre and record release date allowed much better generalization performance and explained up to 50% of shared variance (R²) between observations and model predictions. Overall, the results of this study empirically demonstrate that both acoustic features related to timbre as well as higher level categorical features such as musical genre play a major role in the perception of short music clips.

SUBMITTER: Siedenburg K

PROVIDER: S-EPMC5405345 | biostudies-literature | 2017

REPOSITORIES: biostudies-literature

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Modeling Timbre Similarity of Short Music Clips.

Siedenburg Kai K Müllensiefen Daniel D

Frontiers in psychology 20170426

There is evidence from a number of recent studies that most listeners are able to extract information related to song identity, emotion, or genre from music excerpts with durations in the range of tenths of seconds. Because of these very short durations, timbre as a multifaceted auditory attribute appears as a plausible candidate for the type of features that listeners make use of when processing short music excerpts. However, the importance of timbre in listening tasks that involve short excerp ...[more]

PMID: 28491045

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Project 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.

Dataset Information

Modeling Timbre Similarity of Short Music Clips.

Publications

Modeling Timbre Similarity of Short Music Clips.

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