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Blind estimation of speech transmission index and room acoustic parameters based on the extended model of room impulse response
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Document Title
Blind estimation of speech transmission index and room acoustic parameters based on the extended model of room impulse response
Author
Duangpummet S., Karnjana J., Kongprawechnon W., Unoki M.
Name from Authors Collection
Affiliations
School of Information Science, Japan Advanced Institute of Science and Technology, Japan; National Science and Technology Development Agency, Thailand; Sirindhorn International Institute of Technology, Thammasat University, Thailand
Type
Article
Source Title
Applied Acoustics
ISSN
0003682X
Year
2022
Volume
185
Open Access
Hybrid Gold
Publisher
Elsevier Ltd
DOI
10.1016/j.apacoust.2021.108372
Abstract
The speech transmission index (STI) and room-acoustic parameters, such as the reverberation time and clarity index, are essential to assess the quality of room acoustics. However, in everyday spaces occupied by people, it is difficult to obtain such parameters since the room impulse response (RIR) cannot be measured. Blind estimation of room acoustic parameters from observed signals without measuring RIR is therefore necessary. Although existing methods can estimate one of these parameters, a single parameter is inadequate to describe comprehensive subjective aspects. To this end, this paper proposes a method for estimating STI and five room-acoustic parameters simultaneously. The temporal amplitude envelope of a reverberant speech signal is mapped to the parameters of an RIR model for each sub-band. Instead of using Schroeder's RIR model, the extended RIR model is used to approximate an unknown RIR so that the STI and room-acoustic parameters can be derived. We performed simulations to evaluate the proposed method in unseen reverberant environments. The root-mean-square errors between the ground-truths and estimated parameters suggest that the accuracy of the proposed scheme outperformed that with Schroeder's RIR model and was close to the standard measurements. © 2021 Elsevier Ltd
Industrial Classification
Knowledge Taxonomy Level 1
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Knowledge Taxonomy Level 3
Funding Sponsor
Ministry of Internal Affairs and Communications
License
CC BY-NC-ND
Rights
Elsevier B.V.
Publication Source
Scopus