Modeling binaural unmasking of speech using a blind binaural processing stage
CF Hauth, SC Berning, B Kollmeier… - Trends in …, 2020 - journals.sagepub.com
The equalization cancellation model is often used to predict the binaural masking level
difference. Previously its application to speech in noise has required separate knowledge …
difference. Previously its application to speech in noise has required separate knowledge …
Modeling sluggishness in binaural unmasking of speech for maskers with time-varying interaural phase differences
CF Hauth, T Brand - Trends in hearing, 2018 - journals.sagepub.com
In studies investigating binaural processing in human listeners, relatively long and task-
dependent time constants of a binaural window ranging from 10 ms to 250 ms have been …
dependent time constants of a binaural window ranging from 10 ms to 250 ms have been …
Nonintrusive speech intelligibility prediction using convolutional neural networks
Speech Intelligibility Prediction (SIP) algorithms are becoming popular tools within the
development and operation of speech processing devices and algorithms. However, many …
development and operation of speech processing devices and algorithms. However, many …
Binaural unmasking and spatial release from masking
JF Culling, M Lavandier - Binaural Hearing: With 93 Illustrations, 2021 - Springer
Spatial release from masking (SRM) occurs when a target signal and competing masker
come from different directions. For a stationary noise interferer, it comprises an improvement …
come from different directions. For a stationary noise interferer, it comprises an improvement …
Monaural speech enhancement using deep neural networks by maximizing a short-time objective intelligibility measure
In this paper we propose a Deep Neural Network (D NN) based Speech Enhancement (SE)
system that is designed to maximize an approximation of the Short-Time Objective …
system that is designed to maximize an approximation of the Short-Time Objective …
Refinement and validation of the binaural short time objective intelligibility measure for spatially diverse conditions
Speech intelligibility prediction methods have recently gained popularity in the speech
processing community as supplements to time consuming and costly listening experiments …
processing community as supplements to time consuming and costly listening experiments …
[HTML][HTML] Non-intrusive speech intelligibility prediction using an auditory periphery model with hearing loss
Speech intelligibility prediction methods are necessary for hearing aid development.
However, many such prediction methods are categorized as intrusive metrics because they …
However, many such prediction methods are categorized as intrusive metrics because they …
A non-intrusive short-time objective intelligibility measure
We propose a non-intrusive intelligibility measure for noisy and non-linearly processed
speech, ie a measure which can predict intelligibility from a degraded speech signal without …
speech, ie a measure which can predict intelligibility from a degraded speech signal without …
[HTML][HTML] Personalized signal-independent beamforming for binaural hearing aids
The effect of personalized microphone array calibration on the performance of hearing aid
beamformers under noisy reverberant conditions is studied. The study makes use of a new …
beamformers under noisy reverberant conditions is studied. The study makes use of a new …
A neural network for monaural intrusive speech intelligibility prediction
Monaural intrusive speech intelligibility prediction (SIP) methods aim to predict the speech
intelligibility (SI) of a single-microphone noisy and/or processed speech signal using the …
intelligibility (SI) of a single-microphone noisy and/or processed speech signal using the …