A simple correlation-based model of intelligibility for nonlinear speech enhancement and separation. - Jesper Bünsow Boldt; Daniel P. W. Ellis (EUSIPCO, 2009)

Robust isolated speech recognition using binary masks. - Seliz Gulsen Karadogan; Jan Larsen; Michael Syskind Pedersen; Jesper Bünsow Boldt (EUSIPCO, 2010)

Speech intelligibility of ideal binary masked mixtures. - Ulrik Kjems; Michael Syskind Pedersen; Jesper Bünsow Boldt; Thomas Lunner; DeLiang Wang (EUSIPCO, 2010)

Error-correction of binary masks using hidden Markov models. - Jesper Bünsow Boldt; Michael Syskind Pedersen; Ulrik Kjems; Mads Græsbøll Christensen; Søren Holdt Jensen (ICASSP, 2010)

Single channel speech enhancement in the modulation domain: New insights in the modulation channel selection framework. - Jesper Bünsow Boldt; Andreas T. Bertelsen; Fredrik Gran; Søren Jørgensen; Torsten Dau (ICASSP, 2015)

Semi-non-intrusive objective intelligibility measure using spatial filtering in hearing aids. - Charlotte Sorensen; Jesper Bünsow Boldt; Fredrik Gran; Mads Græsbøll Christensen (EUSIPCO, 2016)

Experimental study of generalized subspace filters for the cocktail party situation. - Knud B. Christensen; Mads Græsbøll Christensen; Jesper Bünsow Boldt; Fredrik Gran (ICASSP, 2016)

Kalman filter for speech enhancement in cocktail party scenarios using a codebook-based approach. - Mathew Shaji Kavalekalam; Mads Græsbøll Christensen; Fredrik Gran; Jesper Bünsow Boldt (ICASSP, 2016)

Binaural speech enhancement using a codebook based approach. - Mathew Shaji Kavalekalam; Mads Græsbøll Christensen; Jesper Bünsow Boldt (IWAENC, 2016)

Non-intrusive intelligibility prediction using a codebook-based approach. - Charlotte Sorensen; Mathew Shaji Kavalekalam; Angeliki Xenaki; Jesper Bünsow Boldt; Mads Græsbøll Christensen (EUSIPCO, 2017)

Model based binaural enhancement of voiced and unvoiced speech. - Mathew Shaji Kavalekalam; Mads Græsbøll Christensen; Jesper Bünsow Boldt (ICASSP, 2017)

Pitch-based non-intrusive objective intelligibility prediction. - Charlotte Sorensen; Angeliki Xenaki; Jesper Bünsow Boldt; Mads Græsbøll Christensen (ICASSP, 2017)

Model Based Estimation of STP Parameters for Binaural Speech Enhancement. - Mathew Shaji Kavalekalam; Jesper Kjær Nielsen; Mads Græsbøll Christensen; Jesper Bünsow Boldt (EUSIPCO, 2018)

Online Parametric NMF for Speech Enhancement. - Mathew Shaji Kavalekalam; Jesper Kjær Nielsen; Liming Shi; Mads Græsbøll Christensen; Jesper Bünsow Boldt (EUSIPCO, 2018)

A Study of Noise PSD Estimators for Single Channel Speech Enhancement. - Mathew Shaji Kavalekalam; Jesper Kjær Nielsen; Mads Græsbøll Christensen; Jesper Bünsow Boldt (ICASSP, 2018)

Model-Based Noise PSD Estimation from Speech in Non-Stationary Noise. - Jesper Kjær Nielsen; Mathew Shaji Kavalekalam; Mads Græsbøll Christensen; Jesper Bünsow Boldt (ICASSP, 2018)

Non-intrusive codebook-based intelligibility prediction. - Charlotte Sorensen; Mathew Shaji Kavalekalam; Angeliki Xenaki; Jesper Bünsow Boldt; Mads Græsbøll Christensen (Speech Commun., 2018)

Hearing Aid-controlled Beamformer for Binaural Speech Enhancement Using a Model-based Approach. - Mathew Shaji Kavalekalam; Jesper Kjær Nielsen; Mads Græsbøll Christensen; Jesper Bünsow Boldt (ICASSP, 2019)

Harmonic Beamformers for Non-Intrusive Speech Intelligibility Prediction. - Charlotte Sørensen; Jesper Bünsow Boldt; Mads Græsbøll Christensen (INTERSPEECH, 2019)

Validation of the Non-Intrusive Codebook-Based Short Time Objective Intelligibility Metric for Processed Speech. - Charlotte Sørensen; Jesper Bünsow Boldt; Mads Græsbøll Christensen (INTERSPEECH, 2019)

Model-Based Speech Enhancement for Intelligibility Improvement in Binaural Hearing Aids. - Mathew Shaji Kavalekalam; Jesper Kjær Nielsen; Jesper Bünsow Boldt; Mads Græsbøll Christensen (IEEE ACM Trans. Audio Speech Lang. Process., 2019)

An Analysis of Traditional Noise Power Spectral Density Estimators Based on the Gaussian Stochastic Volatility Model. - Jesper Kjær Nielsen; Mads Græsbøll Christensen; Jesper Bünsow Boldt (IEEE ACM Trans. Audio Speech Lang. Process., 2023)