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The Speech Intelligibility Index (SII) estimates speech intelligibility based on the audibility of speech cues across frequency. The frequency importance function gives the relative contribution to the SII of the speech audibility at different frequencies. The frequency importance function is usually estimated from the intelligibility data using a complicated multi-step procedure. This paper presents a new procedure for computing the frequency importance function directly from the intelligibility data based on nonlinear joint optimization of the frequency importance function and the SII curve-fitting parameters. An example of using the new approach is presented for previously published W-22 word list intelligibility data.


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