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 …
DNSMOS: 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. The …
human perception. Perceptual objective metrics serve as a proxy for subjective scores. The …
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 …
Deep learning-based non-intrusive multi-objective speech assessment model with cross-domain features
This study proposes a cross-domain multi-objective speech assessment model, called
MOSA-Net, which can simultaneously estimate the speech quality, intelligibility, and …
MOSA-Net, which can simultaneously estimate the speech quality, intelligibility, and …
NORESQA: A framework for speech quality assessment using non-matching references
The perceptual task of speech quality assessment (SQA) is a challenging task for machines
to do. Objective SQA methods that rely on the availability of the corresponding clean …
to do. Objective SQA methods that rely on the availability of the corresponding clean …
Torchaudio-squim: Reference-less speech quality and intelligibility measures in torchaudio
Measuring quality and intelligibility of a speech signal is usually a critical step in
development of speech processing systems. To enable this, a variety of metrics to measure …
development of speech processing systems. To enable this, a variety of metrics to measure …
A study on incorporating Whisper for robust speech assessment
This research introduces an enhanced version of the multi-objective speech assessment
model–MOSA-Net+, by leveraging the acoustic features from Whisper, a large-scaled …
model–MOSA-Net+, by leveraging the acoustic features from Whisper, a large-scaled …
Metricnet: Towards improved modeling for non-intrusive speech quality assessment
The objective speech quality assessment is usually conducted by comparing received
speech signal with its clean reference, while human beings are capable of evaluating the …
speech signal with its clean reference, while human beings are capable of evaluating the …