Computational models of sound-quality metrics using method for calculating loudness with gammatone/gammachirp auditory filterbank
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Sound-quality metrics (SQMs), such as sharpness, roughness, and fluctuation strength, are calculated using a standard method for calculating loudness (Zwicker method, ISO532B, 1975). Since ISO 532 had been revised to contain the Zwicker method (ISO 5321) and Moore-Glasberg method (ISO 532-2) in 2017, the classical computational SQM model should also be revised in accordance with these revisions. A roex auditory filterbank used with the Moore-Glasberg method is defined separately in the frequency domain not to have impulse responses. It is therefore difficult to construct a computational SQM model, e.g., the classical computational SQM model, on the basis of ISO 532-2. We propose a method for calculating loudness using the time-domain gammatone or gammachirp auditory filterbank instead of the roex auditory filterbank to solve this problem. We also propose three computational SQM models based on ISO 532-2 to use with the proposed loudness method. We evaluated the root-mean squared errors (RMSEs) of the calculated loudness with the proposed and Moore-Glasberg methods. We then evaluated the RMSEs of the calculated SQMs with the proposed method and human data of SQMs. We found that the proposed method can be considered as a time-domain method for calculating loudness on the basis of ISO 532-2 because the RMSEs are very small. We also found that the proposed computational SQM models can effectively account for the human data of SQMs compared with the classical computational SQM model in terms of RMSEs.
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