An improved speech transmission index for intelligibility prediction
The speech transmission index (STI) is a well known measure of intelligibility, most suited to the evaluation of speech intelligibility in rooms, with stimuli subjected to additive noise and reverberance. However, STI and its many variations do not effectively represent the intelligibility of stimuli containing non-linear distortions such as those resulting from processing by enhancement algorithms. In this paper, we revisit the STI approach and propose a variation which processes the modulation envelope in short-time segments, requiring only an assumption of quasi-stationarity (rather than the stationarity assumption of STI) of the modulation signal. Results presented in this work show that the proposed approach improves the measures correlation to subjective intelligibility scores compared to traditional STI for a range of noise types and subjected to different enhancement approaches. The approach is also shown to have higher correlation than other coherence, correlation and distance measures tested, but is unsuited to the evaluation of stimuli heavily distorted with (for example) masking based processing, where an alternative approach such as STOI is recommended.