Microscopic Multilingual Matrix Test Predictions Using an ASR-Based Speech Recognition Model

Marc René Schädler, David Hülsmeier, Anna Warzybok, Sabine Hochmuth, Birger Kollmeier


In an attempt to predict the outcomes of matrix sentence tests in different languages and various noise conditions for native listeners, the simulation framework for auditory discrimination experiments (FADE) and the extended Speech Intelligibility Index (eSII) is employed. FADE uses an automatic speech recognition system to simulate recognition experiments and reports the highest achievable performance as the outcome, which showed good predictions for the German matrix test in noise. The eSII is based on the short-time analysis of weighted signal-to-noise ratios in different frequency bands. In contrast to many other approaches, including the eSII, FADE uses no empirical reference. In this work, the FADE approach is evaluated for predictions of the German, Polish, Russian, and Spanish matrix test in stationary and fluctuating noise conditions. The FADE-based predictions yield a high correlation (Pearsons R2 = 0.94) with the empirical data and a root-mean-square (RMS) prediction error of 1.9 dB outperforming the eSII-based predictions (R2 = 0.78, RMS = 4.2 dB). FADE can also predict the data of subgroups with only stationary or only fluctuating noises, while the eSII cannot. The FADE-based predictions seem to generalize over different languages and noise conditions.


DOI: 10.21437/Interspeech.2016-1119

Cite as

Schädler, M.R., Hülsmeier, D., Warzybok, A., Hochmuth, S., Kollmeier, B. (2016) Microscopic Multilingual Matrix Test Predictions Using an ASR-Based Speech Recognition Model. Proc. Interspeech 2016, 610-614.

Bibtex
@inproceedings{Schädler+2016,
author={Marc René Schädler and David Hülsmeier and Anna Warzybok and Sabine Hochmuth and Birger Kollmeier},
title={Microscopic Multilingual Matrix Test Predictions Using an ASR-Based Speech Recognition Model},
year=2016,
booktitle={Interspeech 2016},
doi={10.21437/Interspeech.2016-1119},
url={http://dx.doi.org/10.21437/Interspeech.2016-1119},
pages={610--614}
}