Neural analysis and synthesis: Reconstructing speech from self-supervised representations
We present a neural analysis and synthesis (NANSY) framework that can manipulate the
voice, pitch, and speed of an arbitrary speech signal. Most of the previous works have …
voice, pitch, and speed of an arbitrary speech signal. Most of the previous works have …
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 …
MBNet: MOS prediction for synthesized speech with mean-bias network
Mean opinion score (MOS) is a popular subjective metric to assess the quality of
synthesized speech, and usually involves multiple human judges to evaluate each speech …
synthesized speech, and usually involves multiple human judges to evaluate each speech …
Predictions of subjective ratings and spoofing assessments of voice conversion challenge 2020 submissions
The Voice Conversion Challenge 2020 is the third edition under its flagship that promotes
intra-lingual semiparallel and cross-lingual voice conversion (VC). While the primary …
intra-lingual semiparallel and cross-lingual voice conversion (VC). While the primary …
A review on subjective and objective evaluation of synthetic speech
Evaluating synthetic speech generated by machines is a complicated process, as it involves
judging along multiple dimensions including naturalness, intelligibility, and whether the …
judging along multiple dimensions including naturalness, intelligibility, and whether the …
SQuId: Measuring speech naturalness in many languages
Much of text-to-speech research relies on human evaluation. This incurs heavy costs and
slows down the development process, especially in heavily multilingual applications where …
slows down the development process, especially in heavily multilingual applications where …
Fusion of self-supervised learned models for MOS prediction
We participated in the mean opinion score (MOS) prediction challenge, 2022. This
challenge aims to predict MOS scores of synthetic speech on two tracks, the main track and …
challenge aims to predict MOS scores of synthetic speech on two tracks, the main track and …
InQSS: a speech intelligibility and quality assessment model using a multi-task learning network
Speech intelligibility and quality assessment models are essential tools for researchers to
evaluate and improve speech processing models. However, only a few studies have …
evaluate and improve speech processing models. However, only a few studies have …
Non-Intrusive Speech Quality Assessment Based on Deep Neural Networks for Speech Communication
M Liu, J Wang, F Wang, F Xiang… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Traditionally, speech quality evaluation relies on subjective assessments or intrusive
methods that require reference signals or additional equipment. However, over recent years …
methods that require reference signals or additional equipment. However, over recent years …
Coded Speech Quality Measurement by a Non-Intrusive PESQ-DNN
Wideband codecs such as AMR-WB or EVS are widely used in (mobile) speech
communication. Evaluation of coded speech quality is often performed subjectively by an …
communication. Evaluation of coded speech quality is often performed subjectively by an …