Pitch-based non-intrusive objective intelligibility prediction
Charlotte Sorensen, Angeliki Xenaki, Jesper Bünsow Boldt, Mads Græsbøll Christensen
Abstract
Automatic adjustment of the hearing aid according to the intelligibility for the user in the environment could be beneficial. While most intelligibility metrics require a clean speech reference, i.e. intrusive methods, this is rarely available in real-life. This paper proposes a non-intrusive intelligibility metric in which a reconstruction of the clean speech is used in the established intrusive short-time objective intelligibility (STOI) metric. The reconstruction of the clean speech is based on pitch-features of the desired source using a spatio-temporal harmonic model. This model takes advantage of both the spatial and spectral separation of the desired source and interferers to reconstruct the clean signal. The simulations show a high correlation between the proposed pitch-based STOI (PB-STOI) and the original intrusive STOI and hence is promising for online processing of intelligibility.
BibTeX
@inproceedings{icassp2017_pitchbasednonint,
title = {Pitch-based non-intrusive objective intelligibility prediction},
author = {Charlotte Sorensen and Angeliki Xenaki and Jesper Bünsow Boldt and Mads Græsbøll Christensen},
booktitle = {ICASSP 2017},
year = {2017}
}