278 citations · 372 across the 9 of their papers we have counts for
10 papers
Offline to Online Learning for Real-Time Bandwidth Estimation
Aashish Gottipati, Sami Khairy, Gabriel Mittag +2
Real-time video applications require accurate bandwidth estimation (BWE) to maintain user experience across varying network conditions. However, increasing network heterogeneity ch…
LSTM-based Video Quality Prediction Accounting for Temporal Distortions in Videoconferencing Calls
Gabriel Mittag, Babak Naderi, Vishak Gopal +1
Current state-of-the-art video quality models, such as VMAF, give excellent prediction results by comparing the degraded video with its reference video. However, they do not consid…
ConferencingSpeech 2022 Challenge: Non-intrusive Objective Speech Quality Assessment (NISQA) Challenge for Online Conferencing Applications
Gaoxiong Yi, Wei Xiao, Yiming Xiao +10
With the advances in speech communication systems such as online conferencing applications, we can seamlessly work with people regardless of where they are. However, during online…
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…
Effect of Language Proficiency on Subjective Evaluation of Noise Suppression Algorithms
Babak Naderi, Gabriel Mittag, Rafael Zequeira Jim\a'enez +1
Speech communication systems based on Voice-over-IP technology are frequently used by native as well as non-native speakers of a target language, e.g. in international phone calls…
DNN No-Reference PSTN Speech Quality Prediction
Gabriel Mittag, Ross Cutler, Yasaman Hosseinkashi +4
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.…