no code implementations • 11 Jan 2023 • Christoph Lüscher, Jingjing Xu, Mohammad Zeineldeen, Ralf Schlüter, Hermann Ney
By further adding neural speaker embeddings, we gain additional ~3% relative WER improvement on Hub5'00.
no code implementations • 11 Nov 2022 • Wei Zhou, Haotian Wu, Jingjing Xu, Mohammad Zeineldeen, Christoph Lüscher, Ralf Schlüter, Hermann Ney
Detailed analysis and experimental verification are conducted to show the optimal positions in the ASR neural network (NN) to apply speaker enhancing and adversarial training.
no code implementations • 26 Oct 2022 • Peter Vieting, Christoph Lüscher, Julian Dierkes, Ralf Schlüter, Hermann Ney
Unsupervised representation learning has recently helped automatic speech recognition (ASR) to tackle tasks with limited labeled data.
Automatic Speech Recognition Automatic Speech Recognition (ASR) +3
no code implementations • 24 Oct 2022 • Christoph Lüscher, Mohammad Zeineldeen, Zijian Yang, Tina Raissi, Peter Vieting, Khai Le-Duc, Weiyue Wang, Ralf Schlüter, Hermann Ney
Language barriers present a great challenge in our increasingly connected and global world.
no code implementations • 26 Jun 2022 • Mohammad Zeineldeen, Jingjing Xu, Christoph Lüscher, Ralf Schlüter, Hermann Ney
In this work, we investigate various methods for speaker adaptive training (SAT) based on feature-space approaches for a conformer-based acoustic model (AM) on the Switchboard 300h dataset.
Automatic Speech Recognition Automatic Speech Recognition (ASR) +1
no code implementations • 5 Nov 2021 • Mohammad Zeineldeen, Jingjing Xu, Christoph Lüscher, Wilfried Michel, Alexander Gerstenberger, Ralf Schlüter, Hermann Ney
The recently proposed conformer architecture has been successfully used for end-to-end automatic speech recognition (ASR) architectures achieving state-of-the-art performance on different datasets.
Automatic Speech Recognition Automatic Speech Recognition (ASR) +1
no code implementations • 9 Apr 2021 • Peter Vieting, Christoph Lüscher, Wilfried Michel, Ralf Schlüter, Hermann Ney
With the success of neural network based modeling in automatic speech recognition (ASR), many studies investigated acoustic modeling and learning of feature extractors directly based on the raw waveform.
Automatic Speech Recognition Automatic Speech Recognition (ASR) +2
2 code implementations • 8 May 2019 • Christoph Lüscher, Eugen Beck, Kazuki Irie, Markus Kitza, Wilfried Michel, Albert Zeyer, Ralf Schlüter, Hermann Ney
To the best knowledge of the authors, the results obtained when training on the full LibriSpeech training set, are the best published currently, both for the hybrid DNN/HMM and the attention-based systems.
Ranked #24 on Speech Recognition on LibriSpeech test-other
Automatic Speech Recognition Automatic Speech Recognition (ASR) +3