We proposed and evaluated a speech intelligibility estimation method that does not require
a clean speech reference signal. The propose method uses the features defined in the ITU-T …

We investigated a single-ended speech intelligibility estimation method that does not require
clean speech reference signal, using the features defined in the ITU-T standard P. 563. We …

In this paper, a method to estimate the subjective speech intelligibility scores of the
Japanese DRT speech intelligibility test using some objective measures is proposed and …

We attempted to estimate subjective scores of the Japanese Diagnostic Rhyme Test (DRT),
a two-to-one forced selection speech intelligibility test. We used automatic speech …

This paper discusses a learning approach to predict speech intelligibility in a non-intrusive
manner. The difference in the objective intelligibility of a speech signal and its distorted …

We present NISI, a novel non-intrusive speech intelligibility assessment method based on
feature extraction and a binary tree regression model. A training method using the intrusive …

We attempted to improve the estimated intelligibility scores of the Japanese Diagnostic
Rhyme Test (DRT), a two-to-one forced selection speech intelligibility test, using automatic …

A novel data-driven non-intrusive method to assess speech intelligibility is proposed. The
approach uses a new segment-based feature called Sum-Sorted Spectrogram (SSS) and a …

Methods for estimating speech intelligibility are classified into two types. One is the full
reference method that estimates the subjective evaluation values using both degraded …

This paper presents a deep learning-based non-intrusive speech intelligibility estimation
method using bottleneck features of autoencoder. The conventional standard non-intrusive …