Search Results for author: Babak Naderi

Found 6 papers, 5 papers with code

Bias-Aware Loss for Training Image and Speech Quality Prediction Models from Multiple Datasets

2 code implementations20 Apr 2021 Gabriel Mittag, Saman Zadtootaghaj, Thilo Michael, Babak Naderi, Sebastian Möller

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.

Speech Quality

NISQA: A Deep CNN-Self-Attention Model for Multidimensional Speech Quality Prediction with Crowdsourced Datasets

1 code implementation19 Apr 2021 Gabriel Mittag, Babak Naderi, Assmaa Chehadi, Sebastian Möller

In this paper, we present an update to the NISQA speech quality prediction model that is focused on distortions that occur in communication networks.

Speech Quality

Subjective Evaluation of Noise Suppression Algorithms in Crowdsourcing

1 code implementation25 Oct 2020 Babak Naderi, Ross Cutler

The quality of the speech communication systems, which include noise suppression algorithms, are typically evaluated in laboratory experiments according to the ITU-T Rec.

Speech Quality

Impact of the Number of Votes on the Reliability and Validity of Subjective Speech Quality Assessment in the Crowdsourcing Approach

1 code implementation25 Mar 2020 Babak Naderi, Tobias Hossfeld, Matthias Hirth, Florian Metzger, Sebastian Möller, Rafael Zequeira Jiménez

The subjective quality of transmitted speech is traditionally assessed in a controlled laboratory environment according to ITU-T Rec.


Subjective Assessment of Text Complexity: A Dataset for German Language

no code implementations16 Apr 2019 Babak Naderi, Salar Mohtaj, Kaspar Ensikat, Sebastian Möller

This paper presents TextComplexityDE, a dataset consisting of 1000 sentences in German language taken from 23 Wikipedia articles in 3 different article-genres to be used for developing text-complexity predictor models and automatic text simplification in German language.

Text Simplification

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