The Semantic Space of Vehicle Sounds - An Approach to Develop a Semantic Differential in View of Customer Perceptions

The models that relate noise annoyance assessments to noise signal parameters are mainly based on energy-related indices (e.g., LDEN). However, various studies have shown that sound characteristics of environmental noises linked to temporal and spectral signal features also influence noise annoyance responses. In order to enhance noise annoyance models, an adequate perception-related characterization of these influential acoustical features is essential. On the basis of urban road single-vehicle pass-by noises, this study will show the identification of noise characteristics that rely on spectral and temporal signal properties and that are related to noise annoyance. Based on a semantic differential test with a verbalization task, it will be shown that the sensation dull/shrill, related to the spectral content of the noises and the modulation-related sensations sputtering and nasal are linked to annoyance. The sensation dull/shrill could be characterized using the index TETC (Total Energy of Tonal Components within critical bands from 16 to 24 barks). The correlation of sputtering and nasal sensations with psychoacoustic indices was unsatisfactory. Two alternative indices are proposed to improve the characterization of these specific sensations. It is shown that noise annoyance assessment benefits from taking the TETC index and the sputtering and nasal indices into account.

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“…19 The following items found in literature were also included: "slow/fast" (Ref. 20), "dynamic" (Ref. 21), and "bright" (Ref.…”

Section: Items Of the Semantic Differentialmentioning

confidence: 99%

Spectral and modulation indices for annoyance-relevant features of urban road single-vehicle pass-by noises

Klein

Marquis‐Favre

Weber

et al. 2015

The Journal of the Acoustical Society of America

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“…Altinsoy and Jekosch [33] 2012 Timbre contains complex information concerning the source of a sound. Humans can perform a series of tasks to recognize objects by listening to these sounds [38].…”

Section: Pairsmentioning

confidence: 99%

Analysis and Modeling of Timbre Perception Features in Musical Sounds

et al. 2020

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A novel technique is proposed for the analysis and modeling of timbre perception features, including a new terminology system for evaluating timbre in musical instruments. This database consists of 16 expert and novice evaluation terms, including five pairs with opposite polarity. In addition, a material library containing 72 samples (including 37 Chinese orchestral instruments, 11 Chinese minority instruments, and 24 Western orchestral instruments) and a 54-sample objective acoustic parameter set were developed as part of the study. The method of successive categories was applied to each term for subjective assessment. A mathematical model of timbre perception features (i.e., bright or dark, raspy or mellow, sharp or vigorous, coarse or pure, and hoarse or consonant) was then developed for the first time using linear regression, support vector regression, a neural network, and random forest algorithms. Experimental results showed the proposed model accurately predicted these attributes. Finally, an improved technique for 3D timbre space construction is proposed. Auditory perception attributes for this 3D timbre space were determined by analyzing the correlation between each spatial dimension and the 16 timbre evaluation terms.

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“…A total of 66 sound stimuli were used in this investigation. To elicit the verbal descriptors, the multi-sequential systematic approach described in [14], was used. In the training session, users pressed the buttons of the above devices, made text entries using different keyboards, and surfed the Internet using different mice.…”

Section: Investigation To Determine the Perceptual Attributes Of The mentioning

confidence: 99%

“…In the next step, we checked whether all participants understood these attributes and asked them to evaluate the suitability of these attributes to describe perceptible properties of the button sounds (a detailed description of the investigation steps can be found in [14]). After the understanding and suitability checks, the number of attributes was reduced to 38 (Table 1).…”

Section: Investigation To Determine the Perceptual Attributes Of The mentioning

confidence: 99%

Perceptual features of everyday push button sounds and audiotactile interaction

Altınsoy

2020

Acoust. Sci. & Tech.

Self Cite

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The first aim of this study is to investigate the relationship between the signal properties and the perceptual attributes of everyday push button sounds and the second aim is to investigate the effect of loudness on the perceived tactile feedback intensity from buttons. This knowledge is useful for product designers and sound engineers to find an optimum button sound and haptic feedback for a defined application. In the first step of this study, the physics and signal properties of button sounds are discussed, and an investigation was conducted to determine the users' common language to describe the perceptual properties of everyday button sounds. The results of this investigation showed that the fundamental perceptual factors of button sounds are pleasantness, confirmation, alerting, irritating, and quality. In the next step, a listening experiment was conducted to investigate the relationship between signal properties, such as frequency and damping, and the perceptual factors above. The second part of this study is concerned with auditory-tactile interaction. An experiment was conducted to understand the effect of button sound on the perceived tactile feedback. The results of the experiment clearly show that in bimodal judgments both haptic and auditory information contribute to the perceived tactile strength.

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The Semantic Space of Vehicle Sounds - An Approach to Develop a Semantic Differential in View of Customer Perceptions

Cited by 10 publications

References 1 publication

Spectral and modulation indices for annoyance-relevant features of urban road single-vehicle pass-by noises

Spectral and modulation indices for annoyance-relevant features of urban road single-vehicle pass-by noises

Analysis and Modeling of Timbre Perception Features in Musical Sounds

Perceptual features of everyday push button sounds and audiotactile interaction

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