Signal Processing and Speech Communication Laboratory
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Matthias Zöhrer

Profile Picture Matthias Zöhrer
Student Projects
PhD Thesis
Publications
  • Conference paper Pfeifenberger L., Zöhrer M. & Pernkopf F. (2021) Acoustic Echo Cancellation with Cross-Domain Learning.. [more info]
  • Preprint Pfeifenberger L., Zöhrer M., Roth W., Schindler G., Fröning H. & Pernkopf F. (2020) Resource-Efficient Speech Mask Estimation for Multi-Channel Speech Enhancement.. [more info]
  • Technical report Roth W., Schindler G., Zöhrer M., Pfeifenberger L., Peharz R., Tschiatschek S., Fröning H., Pernkopf F. & Ghahramani Z. (2019) Resource-Efficient Neural Networks for Embedded Systems.. [more info]
  • Conference paper Pfeifenberger L., Zöhrer M. & Pernkopf F. (2019) Deep Complex-valued Neural Beamformers.. [more info]
  • Journal article Pfeifenberger L., Zöhrer M. & Pernkopf F. (2019) Eigenvector-based Speech Mask Estimation for Multi- Channel Speech Enhancement. in IEEE/ACM Transactions on Audio Speech and Language Processing, 27(12), p. 2162 - 2172. [more info] [doi]
  • Journal article Messner E., Zöhrer M. & Pernkopf F. (2018) Heart Sound Segmentation - An Event Detection Approach using Deep Recurrent Neural Networks. in IEEE Transactions on Biomedical Engineering , 65(9), p. 1964-1974. [more info] [doi]
  • Conference paper Schindler G., Zöhrer M., Pernkopf F. & Fröning H. (2018) Towards Efficient Forward Propagation on Resource-Constrained Systems.. [more info]
  • Conference paper Zöhrer M., Pfeifenberger L., Schnindler G., Fröning H. & Pernkopf F. (2018) Resource Efficient Deep Eigenvector Beamforming. (pp. 3354-3358). [more info] [doi]
  • Conference paper Pfeifenberger L., Zöhrer M. & Pernkopf F. (2017) Eigenvector-based Speech Mask Estimation using a Logistic Regression for Multi-Channel Speech Enhancement. in 18th Annual Conference of the International Speech Communication Association (pp. 2660 - 2664). [more info] [doi]
  • Conference paper Zöhrer M. & Pernkopf F. (2017) Virtual Adversarial Training and Data Augmentation for Acoustic Event Detection with Gated Recurrent Neural Networks.. [more info]
  • Conference paper Pfeifenberger L., Zöhrer M. & Pernkopf F. (2017) DNN-based Speech Mask Estimation for Eigenvector Beamforming.. [more info]
  • Conference paper Schrank T., Pfeifenberger L., Zöhrer M., Stahl J., Mowlaee Beikzadehmahaleh P. & Pernkopf F. (2016) Deep Beamforming and Data Augmentation for Robust Speech Recognition: Results of the 4th CHiME Challenge.. [more info]
  • Conference paper Pokorny F., Peharz R., Roth W., Zöhrer M., Pernkopf F., Marschik P. & Schuller B. (2016) Manual Versus Automated: The Challenging Routine of Infant Vocalisation Segmentation in Home Videos to Study Neuro(mal)development. in 17th Annual Conference of the International Speech Communication Association (pp. 2997 - 3001). [more info] [doi]
  • Conference paper Zöhrer M. & Pernkopf F. (2016) Gated Recurrent Networks applied to Acoustic Scene Classification.. [more info]
  • Conference paper Zöhrer M., Pernkopf F. & Peharz R. (2015) On Representation Learning for Artificial Bandwidth Extension. (pp. 791-795). [more info]
  • Conference paper Zöhrer M. & Pernkopf F. (2015) REPRESENTATION MODELS IN SINGLE CHANNEL SOURCE SEPARATION. (pp. 713-717). [more info] [doi]
  • Conference paper Pfeifenberger L., Schrank T., Zöhrer M., Hagmüller M. & Pernkopf F. (2015) Multi-channel speech processing architectures for noise robust speech recognition: 3rd CHiME Challenge results. in 2015 IEEE Workshop on Automatic Speech Recognition & Understanding (pp. 452 - 459). [more info]
  • Journal article Zöhrer M., Pernkopf F. & Peharz R. (2015) Representation Learning for Single-Channel Source Separation and Bandwidth Extension. in IEEE Transactions on Audio Speech and Language Processing , 23(12), p. 2398-2409. [more info] [doi]
  • Conference paper Zöhrer M. & Pernkopf F. (2014) Single-Channel Source Separation with General Stochastic Networks. (pp. x-x). [more info]
  • Conference paper Zöhrer M. & Pernkopf F. (2014) General Stochastic Networks for Classication. (pp. x-x). [more info]