Discriminatively Trained Context-Dependent Duration-Bigram Models for Korean Digit Recognition. - Daniel Willett; Franz Gerl; Raymond Brueckner (ICASSP (1), 2006)

Experiments on Chinese speech recognition with tonal models and pitch estimation using the Mandarin speecon data. - Ying Sun; Daniel Willett; Raymond Brueckner; Rainer Gruhn; Dirk Bühler (INTERSPEECH, 2006)

Language Identification in Vocal Music. - Jochen Schwenninger; Raymond Brueckner; Daniel Willett; Marcus E. Hennecke (ISMIR, 2006)

Comparing Linear Feature Space Transformations for Correlated Features. - Daniel Vásquez; Rainer Gruhn; Raymond Brueckner; Wolfgang Minker (PIT, 2008)

Likability Classification - A Not so Deep Neural Network Approach. - Raymond Brueckner; Björn W. Schuller (INTERSPEECH, 2012)

Hierarchical neural networks and enhanced class posteriors for social signal classification. - Raymond Brueckner; Björn W. Schuller (ASRU, 2013)

Social signal classification using deep blstm recurrent neural networks. - Raymond Brueckner; Björn W. Schuller (ICASSP, 2014)

Adieu features? End-to-end speech emotion recognition using a deep convolutional recurrent network. - George Trigeorgis; Fabien Ringeval; Raymond Brueckner; Erik Marchi; Mihalis A. Nicolaou; Björn W. Schuller; Stefanos Zafeiriou (ICASSP, 2016)

Spotting Social Signals in Conversational Speech over IP: A Deep Learning Perspective. - Raymond Brueckner; Maximilian Schmitt; Maja Pantic; Björn W. Schuller (INTERSPEECH, 2017)

Earlier Identification of Children with Autism Spectrum Disorder: An Automatic Vocalisation-Based Approach. - Florian B. Pokorny; Björn W. Schuller; Peter B. Marschik; Raymond Brueckner; Pär Nyström; Nicholas Cummins; Sven Bölte; Christa Einspieler; Terje Falck-Ytter (INTERSPEECH, 2017)

Asynchronous and Event-Based Fusion Systems for Affect Recognition on Naturalistic Data in Comparison to Conventional Approaches. - Florian Lingenfelser; Johannes Wagner 001; Jun Deng; Raymond Brueckner; Björn W. Schuller; Elisabeth André (IEEE Trans. Affect. Comput., 2018)

Application of Deep Learning Methods in Computational Paralinguistics. - Raymond Brueckner (2020)

EMMI: Empathic Human-Machine Interaction for Establishing Trust in Automated Driving. - Tobias Oetermann; Pia S. C. Dautzenberg; Gudrun Mechthild Irmgard Voß; Christopher Brockmeier; Stefan Ladwig; Patrick Gebhard; Tanja Schneeberger; Markus Funk; Raymond Brueckner; Felix Schäfer; Norbert Helff; Andreas Gomer; et al. (CoRR, 2022)

Detecting Manifest Huntington's Disease Using Vocal Data. - Vinod Subramanian; Namhee Kwon; Raymond Brueckner; Nate Blaylock; Henry O'Connell; Luis Sierra; Clementina Ullman; Karen Hildebrand; Simon E. Laganiere (INTERSPEECH, 2023)

Voice Technology to Identify Fatigue from Japanese Speech. - Raymond Brueckner; Misa Takegami; Namhee Kwon; Nate Blaylock; Vinod Subramanian; Eri Kiyoshige; Soshiro Ogata; Yuriko Nakaoku; Henry O'Connell; Kunihiro Nishimura (SMM, 2023)

Audio-Based Detection of Anxiety and Depression via Vocal Biomarkers. - Raymond Brueckner; Namhee Kwon; Vinod Subramanian; Nate Blaylock; Henry O'Connell (FICC (1), 2024)