A review of deep learning techniques for speech processing
The field of speech processing has undergone a transformative shift with the advent of deep
learning. The use of multiple processing layers has enabled the creation of models capable …
learning. The use of multiple processing layers has enabled the creation of models capable …
Icassp 2023 deep noise suppression challenge
The ICASSP 2023 Deep Noise Suppression (DNS) Challenge marks the fifth edition of the
DNS challenge series. DNS challenges were organized from 2019 to 2023 to foster …
DNS challenge series. DNS challenges were organized from 2019 to 2023 to foster …
NISQA: A deep CNN-self-attention model for multidimensional speech quality prediction with crowdsourced datasets
In this paper, we present an update to the NISQA speech quality prediction model that is
focused on distortions that occur in communication networks. In contrast to the previous …
focused on distortions that occur in communication networks. In contrast to the previous …
DNSMOS P. 835: A non-intrusive perceptual objective speech quality metric to evaluate noise suppressors
Human subjective evaluation is the" gold standard" to evaluate speech quality optimized for
human perception. Perceptual objective metrics serve as a proxy for subjective scores. We …
human perception. Perceptual objective metrics serve as a proxy for subjective scores. We …
Modulation spectral signal representation for quality measurement and enhancement of wearable device data: A technical note
Wearable devices are burgeoning, and applications across numerous verticals are
emerging, including human performance monitoring, at-home patient monitoring, and health …
emerging, including human performance monitoring, at-home patient monitoring, and health …
DNN no-reference PSTN speech quality prediction
Classic public switched telephone networks (PSTN) are often a black box for VoIP network
providers, as they have no access to performance indicators, such as delay or packet loss …
providers, as they have no access to performance indicators, such as delay or packet loss …
A spatial–temporal graph model for pronunciation feature prediction of Chinese poetry
Q Wang, W Liu, X Wang, X Chen… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
With the development of artificial intelligence, speech recognition and prediction have
become one of the important research domains with wild applications, such as intelligent …
become one of the important research domains with wild applications, such as intelligent …
Non-intrusive speech intelligibility prediction for hearing-impaired users using intermediate ASR features and human memory models
R Mogridge, G Close, R Sutherland… - ICASSP 2024-2024 …, 2024 - ieeexplore.ieee.org
Neural networks have been successfully used for non-intrusive speech intelligibility
prediction. Recently, the use of feature representations sourced from intermediate layers of …
prediction. Recently, the use of feature representations sourced from intermediate layers of …
Non-Intrusive Air Traffic Control Speech Quality Assessment with ResNet-BiLSTM
Y Wu, G Li, Q Fu - Applied Sciences, 2023 - mdpi.com
In the current field of air traffic control speech, there is a lack of effective objective speech
quality evaluation methods. This paper proposes a new network framework based on …
quality evaluation methods. This paper proposes a new network framework based on …
The effect of spoken language on speech enhancement using self-supervised speech representation loss functions
Recent work in the field of speech enhancement (SE) has involved the use of self-
supervised speech representations (SSSRs) as feature transformations in loss functions …
supervised speech representations (SSSRs) as feature transformations in loss functions …