2017 INTERSPEECH INTERSPEECH 2017

Predicting Speech Intelligibility Using a Gammachirp Envelope Distortion Index Based on the Signal-to-Distortion Ratio

Abstract

A new intelligibility prediction measure, called “Gammachirp Envelope Distortion Index (GEDI)” is proposed for the evaluation of speech enhancement algorithms. This model calculates the signal-to-distortion ratio (SDR) in envelope responses SDRenv derived from the gammachirp filterbank outputs of clean and enhanced speech, and is an extension of the speech based envelope power spectrum model (sEPSM) to improve prediction and usability. An evaluation was performed by comparing human subjective results and model predictions for the speech intelligibility of noise-reduced sounds processed by spectral subtraction and a recent Wiener filtering technique. The proposed GEDI predicted the subjective results of the Wiener filtering better than those predicted by the original sEPSM and well-known conventional measures, i.e., STOI, CSII, and HASPI.

🧭 Keyword Pioneer — gammachirp filter
🐝 Cross-Pollinator — Artificial Intelligence, Computer Science, Computer Vision, Data Science & Analytics, Deep Learning, Healthcare & Medicine, Interdisciplinary, Machine Learning, Mathematics & Optimization, Natural Language Processing, Robotics, Speech & Audio