Microscopic and Blind Prediction of Speech Intelligibility: Theory and Practice
Author:
Affiliation:
1. Cognitive signal processing group, Electrical engineering department, Ruhr-Universität Bochum, Universitätsstraße 150, Bochum, NRW, Germany
Funder
European Union’s Seventh Framework Programme
REA
NSF
NIH
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
Electrical and Electronic Engineering,Acoustics and Ultrasonics,Computer Science (miscellaneous),Computational Mathematics
Link
https://ieeexplore.ieee.org/ielam/6570655/9657755/9812495-aam.pdf
Reference59 articles.
1. Prediction of speech intelligibility with DNN-based performance measures;martinez;Comput Speech Lang,2022
2. Non-intrusive binaural prediction of speech intelligibility based on phoneme classification;roßbach;Proc Int Conf Acoust Speech Signal Process,0
3. Improving hearing-aid gains based on automatic speech recognition
4. Predicting Speech Perception in Older Listeners with Sensorineural Hearing Loss Using Automatic Speech Recognition
5. DARF: A data-reduced FADE version for simulations of speech recognition thresholds with real hearing aids
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1. Modeling the effect of linguistic predictability on speech intelligibility prediction;JASA Express Letters;2023-03-01
2. Multilingual Non-intrusive Binaural Intelligibility Prediction based on Phone Classification;SSRN Electronic Journal;2023
3. ASR-based speech intelligibility prediction: A review;Hearing Research;2022-12
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