Conferencingspeech 2022 challenge: Non-intrusive objective speech quality assessment (NISQA) challenge for online conferencing applications
With the advances in speech communication systems such as online conferencing
applications, we can seamlessly work with people regardless of where they are. However …
applications, we can seamlessly work with people regardless of where they are. However …
Exploring the influence of fine-tuning data on wav2vec 2.0 model for blind speech quality prediction
Recent studies have shown how self-supervised models can produce accurate speech
quality predictions. Speech representations generated by the pre-trained wav2vec 2.0 …
quality predictions. Speech representations generated by the pre-trained wav2vec 2.0 …
MSQAT: A multi-dimension non-intrusive speech quality assessment transformer utilizing self-supervised representations
Convolutional neural networks (CNNs) have been widely utilized as the main building block
for many non-intrusive speech quality assessment (NISQA) methods. A new trend is to add a …
for many non-intrusive speech quality assessment (NISQA) methods. A new trend is to add a …
MOS-Bench: Benchmarking Generalization Abilities of Subjective Speech Quality Assessment Models
Subjective speech quality assessment (SSQA) is critical for evaluating speech samples as
perceived by human listeners. While model-based SSQA has enjoyed great success thanks …
perceived by human listeners. While model-based SSQA has enjoyed great success thanks …
Efficient speech quality assessment using self-supervised framewise embeddings
Automatic speech quality assessment is essential for audio researchers, developers, speech
and language pathologists, and system quality engineers. The current state-of-the-art …
and language pathologists, and system quality engineers. The current state-of-the-art …
MOSRA: Joint mean opinion score and room acoustics speech quality assessment
The acoustic environment can degrade speech quality during communication (eg, video call,
remote presentation, outside voice recording), and its impact is often unknown. Objective …
remote presentation, outside voice recording), and its impact is often unknown. Objective …
[PDF][PDF] BIT-MI Deep Learning-based Model to Non-intrusive Speech Quality Assessment Challenge in Online Conferencing Applications.
M Liu, J Wang, L Xu, J Zhang, S Li, F Xiang - INTERSPEECH, 2022 - isca-archive.org
This paper presents the details of the BIT-MI deep learningbased model submitted to the
ConferencingSpeech challenge 2022. Due to the large time and labor costs of subjective …
ConferencingSpeech challenge 2022. Due to the large time and labor costs of subjective …
Hallucination in Perceptual Metric-Driven Speech Enhancement Networks
Within the area of speech enhancement, there is an ongoing interest in the creation of
neural systems which explicitly aim to improve the perceptual quality of the processed audio …
neural systems which explicitly aim to improve the perceptual quality of the processed audio …
AlignNet: Learning dataset score alignment functions to enable better training of speech quality estimators
J Pieper, SD Voran - arXiv preprint arXiv:2406.10205, 2024 - arxiv.org
We develop two complementary advances for training no-reference (NR) speech quality
estimators with independent datasets. Multi-dataset finetuning (MDF) pretrains an NR …
estimators with independent datasets. Multi-dataset finetuning (MDF) pretrains an NR …
Non-intrusive speech quality assessment: A survey
Speech quality is a critical consideration for applications such as speech enhancement,
coding, transmission, and synthesis. Accurately evaluating the quality of degraded speech …
coding, transmission, and synthesis. Accurately evaluating the quality of degraded speech …