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Reinhold Haeb-Umbach
Researcher at University of Paderborn
Publications - 297
Citations - 7156
Reinhold Haeb-Umbach is an academic researcher from University of Paderborn. The author has contributed to research in topics: Speech enhancement & Noise. The author has an hindex of 35, co-authored 295 publications receiving 6045 citations. Previous affiliations of Reinhold Haeb-Umbach include Philips.
Papers
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Journal ArticleDOI
An overview of noise-robust automatic speech recognition
TL;DR: A thorough overview of modern noise-robust techniques for ASR developed over the past 30 years is provided and methods that are proven to be successful and that are likely to sustain or expand their future applicability are emphasized.
Journal ArticleDOI
Multiclass linear dimension reduction by weighted pairwise Fisher criteria
TL;DR: A class of computationally inexpensive linear dimension reduction criteria is derived by introducing a weighted variant of the well-known K-class Fisher criterion associated with linear discriminant analysis (LDA).
Proceedings ArticleDOI
Neural network based spectral mask estimation for acoustic beamforming
TL;DR: A neural network based approach to acoustic beamforming is presented, used to estimate spectral masks from which the Cross-Power Spectral Density matrices of speech and noise are estimated, which are used to compute the beamformer coefficients.
Proceedings ArticleDOI
Linear discriminant analysis for improved large vocabulary continuous speech recognition
Reinhold Haeb-Umbach,Hermann Ney +1 more
TL;DR: The interaction of linear discriminant analysis (LDA) and a modeling approach using continuous Laplacian mixture density HMM is studied experimentally and the largest improvements in speech recognition could be obtained when the classes for the LDA transform were defined to be sub-phone units.
Journal ArticleDOI
A summary of the REVERB challenge: state-of-the-art and remaining challenges in reverberant speech processing research
Keisuke Kinoshita,Marc Delcroix,Sharon Gannot,Emanuel A. P. Habets,Reinhold Haeb-Umbach,Walter Kellermann,Volker Leutnant,Roland Maas,Tomohiro Nakatani,Bhiksha Raj,Armin Sehr,Takuya Yoshioka +11 more
TL;DR: The REVERB challenge is described, which is an evaluation campaign that was designed to evaluate such speech enhancement and ASR techniques to reveal the state-of-the-art techniques and obtain new insights regarding potential future research directions.