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Several algorithms have been shown to generate a metric corresponding to the Speech Transmission Index (STI) using speech as a probe stimulus [e.g., Goldsworthy and Greenberg, J. Acoust. Soc. Am. 116, 3679-3689 (2004)]. The time-domain approaches work well on long speech segments and have the added potential to be used for short-time analysis. This study investigates the performance of the Envelope Regression (ER) time-domain STI method as a function of window length, in acoustically degraded environments with multiple talkers and speaking styles. The ER method is compared with a short-time Theoretical STI, derived from octave-band signal-to-noise ratios and reverberation times. For windows as short as 0.3 s, the ER method tracks short-time Theoretical STI changes in stationary speech-shaped noise, fluctuating restaurant babble and stationary noise plus reverberation. The metric is also compared to intelligibility scores on conversational speech and speech articulated clearly but at normal speaking rates (Clear/Norm) in stationary noise. Correlation between the metric and intelligibility scores is high and, consistent with the subject scores, the metrics are higher for Clear/Norm speech than for conversational speech and higher for the first word in a sentence than for the last word.

Comparison of a short-time speech-based intelligibility metric to the speech transmission index and intelligibility data