278 citations · 372 across the 9 of their papers we have counts for
5 papers · 1 filter
Visualising and Explaining Deep Learning Models for Speech Quality Prediction
H. Tilkorn, G. Mittag, S. Möller
Estimating quality of transmitted speech is known to be a non-trivial task. While traditionally, test participants are asked to rate the quality of samples; nowadays, automated met…
Full-Reference Speech Quality Estimation with Attentional Siamese Neural Networks
Gabriel Mittags, Sebastian Möller
In this paper, we present a full-reference speech quality prediction model with a deep learning approach. The model determines a feature representation of the reference and the deg…
Deep Learning Based Assessment of Synthetic Speech Naturalness
Gabriel Mittag, Sebastian Möller
In this paper, we present a new objective prediction model for synthetic speech naturalness. It can be used to evaluate Text-To-Speech or Voice Conversion systems and works languag…
Bias-Aware Loss for Training Image and Speech Quality Prediction Models from Multiple Datasets
Gabriel Mittag, Saman Zadtootaghaj, Thilo Michael +2
The ground truth used for training image, video, or speech quality prediction models is based on the Mean Opinion Scores (MOS) obtained from subjective experiments. Usually, it is…
NISQA: A Deep CNN-Self-Attention Model for Multidimensional Speech Quality Prediction with Crowdsourced Datasets
Gabriel Mittag, Babak Naderi, Assmaa Chehadi +1
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 ve…