Abstract
The aim of the study is to transpose and extend to a set of environmental sounds the notion of sound descriptors usually used for musical sounds. Four separate primary studies dealing with interior car sounds, air-conditioning units, car horns, and closing car doors are considered collectively. The corpus formed by these initial stimuli is submitted to new experimental studies and analyses, both for revealing metacategories and for defining more precisely the limits of each of the resulting categories. In a second step, the new structure is modeled: common and specific dimensions within each category are derived from the initial results and new investigations of audio features are performed. Furthermore, an automatic classifier based on two audio descriptors and a multinomial logistic regression procedure is implemented and validated with the corpus.
Highlights
The purpose of this study is to transpose and extend the timbre description principles from musical sounds to environmental sounds, which are by nature considered as nonmusical
Even though the selected sounds are in the same range of loudness, they were not equalized in loudness
Within the restricted scope of environmental sounds studied here, we are faced with the following structure: (i) a motor category including sounds from 3 different corpora (A1, A2, B), each of them being described by a perceptual space and augmented with perceptually validated new sounds, for a total of 99 items, (ii) an instrument-like category including 22 sounds from corpus C described by a perceptual space and augmented with 27 perceptually validated new sounds, for a total of 49, (iii) an impact category including 12 sounds from corpus D described by a perceptual space and augmented with 47 perceptually validated new sounds, for a total of 59
Summary
The purpose of this study is to transpose and extend the timbre description principles from musical sounds to environmental sounds, which are by nature considered as nonmusical. Within the restricted framework given by the scope of the primary research upon which the present study is based (see Section 2), the final aim is to automate indexing and classification of environmental sounds. The work detailed in this article starts from four primary industrial studies on sound attributes dealing with sounds produced by car engines (Susini et al [2,3,4], McAdams et al [5]), air-conditioning units (Susini et al [6]), car horns (Lemaitre et al [7, 8]), and closing car doors (Parizet et al [9]) The aim of these studies was to apply the methodology developed to study the timbre of musical sounds to a specific category of environmental sounds. The standard methodology used in these studies was based on a multidimensional scaling technique (MDS) applied to dissimilarity ratings
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