Amigo Context Management Service with Applications in Ambient Communication Scenarios. - Joerg Schmalenstroeer; Volker Leutnant; Reinhold Haeb-Umbach (AmI Workshops, 2007)

An analytic derivation of a phase-sensitive observation model for noise robust speech recognition. - Volker Leutnant; Reinhold Haeb-Umbach (INTERSPEECH, 2009)

Fusing audio and video information for online speaker diarization. - Joerg Schmalenstroeer; Martin Kelling; Volker Leutnant; Reinhold Haeb-Umbach (INTERSPEECH, 2009)

On the Initialization of Dynamic Models for Speech Features. - Alexander Krueger; Volker Leutnant; Reinhold Haeb-Umbach; Marcel R. Ackermann; Johannes Blömer (Sprachkommunikation, 2010)

On the exploitation of hidden Markov models and linear dynamic models in a hybrid decoder architecture for continuous speech recognition. - Volker Leutnant; Reinhold Haeb-Umbach (INTERSPEECH, 2010)

Conditional Bayesian Estimation Employing a Phase-Sensitive Observation Model for Noise Robust Speech Recognition. - Volker Leutnant; Reinhold Haeb-Umbach (Robust Speech Recognition of Uncertain or Missing Data, 2011)

A Versatile Gaussian Splitting Approach to Non-Linear State Estimation and its Application to Noise-Robust ASR. - Volker Leutnant; Alexander Krueger; Reinhold Haeb-Umbach (INTERSPEECH, 2011)

Investigations Into a Statistical Observation Model for Logarithmic Mel Power Spectral Density Features of Noisy Reverberant Speech. - Volker Leutnant; Alexander Krueger; Reinhold Haeb-Umbach (ITG Conference on Speech Communication, 2012)

Bayesian Feature Enhancement for ASR of Noisy Reverberant Real-World Data. - Alexander Krueger; Oliver Walter; Volker Leutnant; Reinhold Haeb-Umbach (INTERSPEECH, 2012)

GMM-based significance decoding. - Ahmed Hussen Abdelaziz; Steffen Zeiler; Dorothea Kolossa; Volker Leutnant; Reinhold Haeb-Umbach (ICASSP, 2013)

Bayesian Feature Enhancement for Reverberation and Noise Robust Speech Recognition. - Volker Leutnant; Alexander Krueger; Reinhold Haeb-Umbach (IEEE Trans. Speech Audio Process., 2013)

A New Observation Model in the Logarithmic Mel Power Spectral Domain for the Automatic Recognition of Noisy Reverberant Speech. - Volker Leutnant; Alexander Krueger; Reinhold Haeb-Umbach (IEEE ACM Trans. Audio Speech Lang. Process., 2014)

A summary of the REVERB challenge: state-of-the-art and remaining challenges in reverberant speech processing research. - Keisuke Kinoshita; Marc Delcroix; Sharon Gannot; Emanuël A. P. Habets; Reinhold Haeb-Umbach; Walter Kellermann; Volker Leutnant; Roland Maas; Tomohiro Nakatani; Bhiksha Raj; Armin Sehr; Takuya Yoshioka (EURASIP J. Adv. Signal Process., 2016)

Bayesian estimation employing a phase-sensitive observation model for noise and reverberation robust automatic speech recognition. - Volker Leutnant (2016)

The REVERB Challenge: A Benchmark Task for Reverberation-Robust ASR Techniques. - Keisuke Kinoshita; Marc Delcroix; Sharon Gannot; Emanuël A. P. Habets; Reinhold Haeb-Umbach; Walter Kellermann; Volker Leutnant; Roland Maas; Tomohiro Nakatani; Bhiksha Raj; Armin Sehr; Takuya Yoshioka (New Era for Robust Speech Recognition, Exploiting Deep Learning, 2017)

Acoustic Model Bootstrapping Using Semi-Supervised Learning. - Langzhou Chen; Volker Leutnant (INTERSPEECH, 2019)

Improving Speech Recognition of Compound-Rich Languages. - Prabhat Pandey; Volker Leutnant; Simon Wiesler; Jahn Heymann; Daniel Willett (INTERSPEECH, 2020)

Lattention: Lattice-Attention in ASR Rescoring. - Prabhat Pandey; Sergio Duarte Torres; Ali Orkan Bayer; Ankur Gandhe; Volker Leutnant (ICASSP, 2022)

Promptformer: Prompted Conformer Transducer for ASR. - Sergio Duarte Torres; Arunasish Sen; Aman Rana; Lukas Drude; Alejandro Gómez Alanís; Andreas Schwarz; Leif Rädel; Volker Leutnant (ICASSP, 2024)

Universal Semantic Disentangled Privacy-preserving Speech Representation Learning. - Biel Tura Vecino; Subhadeep Maji; Aravind Varier; Antonio Bonafonte; Ivan Valles; Michael Owen; Leif Rädel; Grant P. Strimel; Seyi Feyisetan; Roberto Barra-Chicote; Ariya Rastrow; Constantinos Papayiannis; et al. (CoRR, 2025)