The speech intelligibility and applicability of the speech transmission index in large spaces

Liu, Hongshan; Ma, Hui; Kang, Jian; Wang, Chao

doi:10.1016/j.apacoust.2020.107400

Cited by 9 publications

(5 citation statements)

References 26 publications

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“…Initial conversations with hospital staff revealed certain annoyances related to the acoustic parameters of reverberation time [42,77] and speech intelligibility [48] in the patient dining area. Specifically, the project nurse characterised the room as "ringing" and described a tendency of the room to accumulate "noise", which, in turn, caused both staff and patients to gradually increase the volume of their speech in order to make themselves heard.…”

Section: Room Acoustics Analysis Treatment and Wall Panel Designmentioning

confidence: 99%

Music Is Served: How Acoustic Interventions in Hospital Dining Environments Can Improve Patient Mealtime Wellbeing

Mathiesen

Aadal

Uldbæk³

et al. 2021

Foods

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Eating-related challenges and discomforts arising from moderately acquired brain injuries (ABI)—including physiological and cognitive difficulties—can interfere with patients’ eating experience and impede the recovery process. At the same time, external environmental factors have been proven to be influential in our mealtime experience. This experimental pilot study investigates whether redesigning the sonic environment in hospital dining areas can positively influence ABI patients’ (n = 17) nutritional state and mealtime experience. Using a three-phase between-subjects interventional design, we investigate the effects of installing sound proofing materials and playing music during the lunch meals at a specialised ABI hospital unit. Comprising both quantitative and qualitative research approaches and data acquisition methods, this project provides multidisciplinary and holistic insights into the importance of attending to sound in hospital surroundings. Our results demonstrate that improved acoustics and music playback during lunch meals might improve the mealtime atmosphere, the patient well-being, and social interaction, which potentially supports patient food intake and nutritional state. The results are discussed in terms of potential future implications for the healthcare sector.

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Section: Room Acoustics Analysis Treatment and Wall Panel Designmentioning

confidence: 99%

Music Is Served: How Acoustic Interventions in Hospital Dining Environments Can Improve Patient Mealtime Wellbeing

Mathiesen

Aadal

Uldbæk³

et al. 2021

Foods

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show abstract

“…In Yang and Mak, 28 subjective speech intelligibility scores and speech transmission index in secondary school and university classrooms have been correlated by regression models. Based on the tests described by Liu et al, 29 the relationship between STI and speech intelligibility in large spaces has been modified, and a new threshold for the STI assessment has been proposed. Peters 30 studied the potential binaural effect of reduced reflection and reverberation, finding that these conditions decrease intelligibility due to echoes and strong discrete delayed reflections and lead to incorrect STI evaluation.…”

Section: Introductionmentioning

confidence: 99%

Assessment of speech intelligibility in scholar classrooms by measurements and prediction methods

et al. 2023

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According to Italian regulation, the Ministerial Decree of 11 October 2017 about Environmental Criteria, reference values for acoustic indoor quality descriptors in public buildings are imposed. Regarding school environments, indoor acoustic quality targets refer to reverberation time, clarity, and speech intelligibility, whose representative acoustic descriptor is the speech transmission index (STI). This paper presents pyeSTImate, a Python-based tool for speech transmission index prediction in lecture rooms. The tool returns fully simulated results from the dimensions and material characteristics of classrooms with parallelepiped geometry and without limitations in size. Extensive experiments have been conducted with different simulation methods, evaluating the accuracy by comparison with in situ measurements selected from primary, secondary, and university classrooms in school buildings of the Marche Region in Italy. The combination of simulated speech transmission indexes with a prediction method based on an artificial neural network has also been evaluated. The analysis of the performance demonstrates the computational robustness of the tool that enables its use for the analysis of existing rooms, as well as for the renovation and design of new spaces.

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“…1 However, there is usually a high level of noise and poor speech intelligibility in large waiting halls. [2][3][4][5] Crowd noise is one of the most important noise sources 3 and influenced by the surrounding environment and crowd characteristics. 6 Thus, it exhibits significant fluctuations in the temporal and spatial dimensions.…”

Section: Introductionmentioning

confidence: 99%

Prediction model of crowd noise in large waiting halls

Liu

Wang

et al. 2022

The Journal of the Acoustical Society of America

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Crowd noise is usually the primary noise in large waiting halls, and it is difficult to predict because it is influenced by several factors such as room acoustics and crowd characteristics. This study developed a crowd noise prediction model based on the superposition of direct and reverberant sound energy using the factors of the spatial layout of waiting halls, number and distribution of crowds, behavior ratio (ratio of vocal passengers to the total number of passengers), and average crowd sound power. To verify the model, on-site measurements were conducted in two large waiting halls to obtain the necessary input parameters. The crowd noise levels in one of the waiting halls were obtained from 1-s noise level data after excluding broadcast periods. A method for determining an individual's average sound power based on the model was also presented and found to be approximately 70.6 dB. Finally, the model was verified using measured data, and it showed that the model could accurately predict the average crowd noise level and changing trend of crowd noise in temporal and spatial dimensions with an average R-square of approximately 0.55 and average difference of approximately 1.1 dBA between the predicted and measured results.

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The speech intelligibility and applicability of the speech transmission index in large spaces

Cited by 9 publications

References 26 publications

Music Is Served: How Acoustic Interventions in Hospital Dining Environments Can Improve Patient Mealtime Wellbeing

Music Is Served: How Acoustic Interventions in Hospital Dining Environments Can Improve Patient Mealtime Wellbeing

Assessment of speech intelligibility in scholar classrooms by measurements and prediction methods

Prediction model of crowd noise in large waiting halls

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