A series of SNR-based speech intelligibility models in the Auditory Modeling Toolbox

Lavandier, Mathieu; Vicente, Thibault; Prud’homme, Luna

doi:10.1051/aacus/2022017

Cited by 10 publications

(9 citation statements)

References 80 publications

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“…For objective acoustic indicators, this study has selected LAeq (A-weighted equivalent continuous sound level) as the primary monitoring metric owing to the discontinuity of park soundscapes [39]. For thermal environment metrics, the Universal Thermal Climate Index (UTCI) was chosen given the instability of outdoor thermal conditions [40].…”

Section: Methodsmentioning

confidence: 99%

Thermal–Acoustic Interaction Impacts on Crowd Behaviors in an Urban Park

Chen,

Lin

et al. 2023

Forests

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As urbanization accelerates, parks, as vital urban public open spaces, and their acoustic and thermal ambience directly impact visitors’ comfort and the sustainability of parks. Selecting Xihu Park in Fuzhou, China located in the subtropical region as a typical example, this study utilizes covert observational experiments with different typical sounds (grass cutting, music, and no sound source) across temperature levels to examine the influence of thermal–acoustic interactions on crowd behaviors in the park. The findings are as follows: (1) melodious music can attract more tourists, while strong stimulating grass cutting noises under high temperatures reduce crowd flow. Excluding unpleasant audio sources, park soundscapes across temperatures have a relatively limited influence on attractiveness to people flow. (2) High temperatures diminish tourists’ interest in landscape experiences and persons staying, especially when the soundscape quality is poorer. Under non-high temperatures, audio environments have a minor impact on the staying time. (3) The soundscape quality plays a role by affecting people’s path choices of approaching or avoiding sound sources, where grass cutting noise has the most negative influence. Music, grass cutting sounds, and natural sounds demonstrate conspicuous differences in their effects under varied temperatures. (4) Comfortable acoustic environments can draw larger crowds and decrease the walking pace. High temperatures make crowds take slower steps. Different sound types have significant influences on crowd movement velocity under three typical temperature levels. This study comprehensively investigates the mechanisms of typical thermal–acoustic environments’ impacts on park crowd behaviors, providing important references for optimizing the acoustic and thermal environments of urban parks, while also enriching related research on landscape design and environmental psychology. Future studies can conduct in-depth explorations by creating more abundant thermal–acoustic combinations and probe differences across diverse populations.

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Section: Methodsmentioning

confidence: 99%

Thermal–Acoustic Interaction Impacts on Crowd Behaviors in an Urban Park

Chen,

Lin

et al. 2023

Forests

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“…In the AMT 1.1, we have loudness models represented by moore1997 [52], glasberg2002 [53], and chen2011 [54] as well as a loudness model considering binaural inhibition, moore2016 [55]. We have monaural speech perception models such as joergensen 2011 [56], taal2011 [57], and joergensen2013 [7], and models considering binaural speech processing such as culling2004 [58], jelfs2011 [59], leclere2015 [60], hauth2020 [61], prudhomme2020 [62], vicente 2020nh [63], vicente2020 [64], and lavandier2022 [65]. For perceptual similarity, we have osses2021 [66] as a monaural model and llado2022 [67] as a binaural model considering the effect of head-worn devices.…”

Section: Perception and Behaviormentioning

confidence: 99%

AMT 1.x: A toolbox for reproducible research in auditory modeling

2022

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The Auditory Modeling Toolbox (AMT) is a MATLAB/Octave toolbox for the development and application of computational auditory models with a particular focus on binaural hearing. The AMT aims for a consistent implementation of auditory models, well-structured in-code documentation, and inclusion of auditory data required to run the models. The motivation is to provide a toolbox able to reproduce the model predictions and allowing students and researchers to work with and to advance existing models. In the AMT, model implementations can be evaluated in two stages: by running so-called demonstrations, which are quick presentations of a model, and by starting so-called experiments aimed at reproducing results from the corresponding publications. Here, we describe the tools and mechanisms available within the framework of all AMT 1.x versions. The recently released AMT 1.1 includes over 60 models and is freely available as an open-source package from https://www.amtoolbox.org.

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“…In many studies related to soundscapes, general evaluations of soundscapes are usually considered to be evaluations of sound levels, that is, the subjective evaluation of loudness, usually of background noise [1][2][3][4][5][6]. Soundscape evaluations are also considered to be evaluations of sound preferences, that is, evaluations of foreground sounds [7][8][9][10][11]. Individual sounds play an important role in the overall soundscape [12].…”

Section: Introductionmentioning

confidence: 99%

Effect of Audio–Visual Factors in the Evaluation of Crowd Noise

Yang

Kang

2023

Applied Sciences

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A crowd can be both a sound source and an absorber. The sound of human voices significantly impacts evaluations of acoustic indicators in urban public spaces. This study aimed to investigate whether human sound impacts evaluations of the overall environment from both visual and auditory aspects. Primary sound sources and scenes in Harbin, China urban public space served as the research object. Four sets of sound sources and six sets of images were collected in situ in urban public spaces. A subjective evaluation of both visual and auditory aspects was then performed in the laboratory. The results showed that when different types of sounds in urban public spaces are superimposed with human sound, the volume of human sound (45.6 dBA, 55.6 dBA, and 65.6 dBA) significantly affects the acoustic evaluation of the environment. When the superimposed sounds were birds and music, the evaluation of the environment decreased with the human voice increasing in volume. Crowd density and the surrounding visual environment also influence evaluations of the overall sound environment. In this study, the sound preference and acoustic comfort of birdsong and music decreased as the human sound volume increased. The effect of human sound combined with traffic sounds significantly decreased the scores for sound preference and acoustic comfort at higher volumes. The results of the experiments on audio–visual interactions in which people evaluated visual scenes showed that the influence of the visual density of a crowd on assessments of the sound environment is negatively related to the magnitude of the sound of the crowd. When human voices are at 45.6 dBA and 65.6dBA, there is a significant effect on the evaluation of visual scenes for high-density people. When the sound pressure level of human voices is the same, changes in the visual environment are more likely to affect people’s evaluation of the overall sound environment.

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A series of SNR-based speech intelligibility models in the Auditory Modeling Toolbox

Cited by 10 publications

References 80 publications

Thermal–Acoustic Interaction Impacts on Crowd Behaviors in an Urban Park

Thermal–Acoustic Interaction Impacts on Crowd Behaviors in an Urban Park

AMT 1.x: A toolbox for reproducible research in auditory modeling

Effect of Audio–Visual Factors in the Evaluation of Crowd Noise

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