A binaural short time objective intelligibility measure for noisy and enhanced speech. - Asger Heidemann Andersen; Jan Mark de Haan; Zheng-Hua Tan; Jesper Jensen 001 (INTERSPEECH, 2015)

A method for predicting the intelligibility of noisy and non-linearly enhanced binaural speech. - Asger Heidemann Andersen; Jan Mark de Haan; Zheng-Hua Tan; Jesper Jensen 001 (ICASSP, 2016)

Speech intelligibility prediction as a classification problem. - Asger Heidemann Andersen; Esther Schoenmaker; Steven van de Par (MLSP, 2016)

Predicting the Intelligibility of Noisy and Nonlinearly Processed Binaural Speech. - Asger Heidemann Andersen; Jan Mark de Haan; Zheng-Hua Tan; Jesper Jensen 001 (IEEE ACM Trans. Audio Speech Lang. Process., 2016)

A non-intrusive Short-Time Objective Intelligibility measure. - Asger Heidemann Andersen; Jan Mark de Haan; Zheng-Hua Tan; Jesper Jensen 001 (ICASSP, 2017)

On the Use of Band Importance Weighting in the Short-Time Objective Intelligibility Measure. - Asger Heidemann Andersen; Jan Mark de Haan; Zheng-Hua Tan; Jesper Jensen 001 (INTERSPEECH, 2017)

Refinement and validation of the binaural short time objective intelligibility measure for spatially diverse conditions. - Asger Heidemann Andersen; Jan Mark de Haan; Zheng-Hua Tan; Jesper Jensen 001 (Speech Commun., 2018)

Nonintrusive Speech Intelligibility Prediction Using Convolutional Neural Networks. - Asger Heidemann Andersen; Jan Mark de Haan; Zheng-Hua Tan; Jesper Jensen 001 (IEEE ACM Trans. Audio Speech Lang. Process., 2018)

A Neural Network for Monaural Intrusive Speech Intelligibility Prediction. - Mathias Bach Pedersen; Asger Heidemann Andersen; Søren Holdt Jensen; Jesper Jensen 001 (ICASSP, 2020)

End-to-End Speech Intelligibility Prediction Using Time-Domain Fully Convolutional Neural Networks. - Mathias Bach Pedersen; Morten Kolbæk; Asger Heidemann Andersen; Søren Holdt Jensen; Jesper Jensen 001 (INTERSPEECH, 2020)

Training Data-Driven Speech Intelligibility Predictors on Heterogeneous Listening Test Data. - Mathias Bach Pedersen; Asger Heidemann Andersen; Søren Holdt Jensen; Zheng-Hua Tan; Jesper Jensen 001 (IEEE Access, 2022)