278 citations · 770 across the 32 of their papers we have counts for
6 papers · 1 filter
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…
Speech Quality Assessment in Crowdsourcing: Comparison Category Rating Method
Babak Naderi, Sebastian Möller, Ross Cutler
Traditionally, Quality of Experience (QoE) for a communication system is evaluated through a subjective test. The most common test method for speech QoE is the Absolute Category Ra…
Incorporating Wireless Communication Parameters into the E-Model Algorithm
Demóstenes Z. Rodríguez, Dick Carrillo Melgarejo, Miguel A. Ramírez +2
Telecommunication service providers have to guarantee acceptable speech quality during a phone call to avoid a negative impact on the users' quality of experience. Currently, there…