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2020 – today
- 2023
[c17]Zhengyang Li, Thomas Graave, Jing Liu, Timo Lohrenz, Siegfried Kunzmann, Tim Fingscheidt:
Parameter-Efficient Cross-Language Transfer Learning for a Language-Modular Audiovisual Speech Recognition. ASRU 2023: 1-8- [c16]Timo Lohrenz, Björn Möller, Zhengyang Li, Tim Fingscheidt:
Relaxed Attention for Transformer Models. IJCNN 2023: 1-10 - [c15]Zhengyang Li, Chenwei Liang, Timo Lohrenz, Marvin Sach, Björn Möller, Tim Fingscheidt:
An Efficient and Noise-Robust Audiovisual Encoder for Audiovisual Speech Recognition. INTERSPEECH 2023: 1583-1587 - 2022
- [c14]Zhengyang Li
, Timo Lohrenz, Matthias Dunkelberg, Tim Fingscheidt:
Transformer-Based Lip-Reading with Regularized Dropout and Relaxed Attention. SLT 2022: 723-730 - [i3]Timo Lohrenz, Björn Möller, Zhengyang Li, Tim Fingscheidt:
Relaxed Attention for Transformer Models. CoRR abs/2209.09735 (2022) - 2021
- [c13]Timo Lohrenz, Patrick Schwarz, Zhengyang Li, Tim Fingscheidt:
Multi-Head Fusion Attention for Transformer-Based End-to-End Automatic Speech Recognition. ITG Conference on Speech Communication 2021: 1-5 - [c12]Timo Lohrenz, Patrick Schwarz, Zhengyang Li, Tim Fingscheidt:
Relaxed Attention: A Simple Method to Boost Performance of End-to-End Automatic Speech Recognition. ASRU 2021: 177-184 - [c11]Jan Baumann, Patrick Meyer, Timo Lohrenz, Alexander Roy, Michael Papendieck, Tim Fingscheidt:
A New DCASE 2017 Rare Sound Event Detection Benchmark Under Equal Training Data: CRNN With Multi-Width Kernels. ICASSP 2021: 865-869 - [c10]Timo Lohrenz, Zhengyang Li, Tim Fingscheidt:
Multi-Encoder Learning and Stream Fusion for Transformer-Based End-to-End Automatic Speech Recognition. Interspeech 2021: 2846-2850 - [i2]Timo Lohrenz, Zhengyang Li, Tim Fingscheidt:
Multi-Encoder Learning and Stream Fusion for Transformer-Based End-to-End Automatic Speech Recognition. CoRR abs/2104.00120 (2021) - [i1]Timo Lohrenz, Patrick Schwarz, Zhengyang Li, Tim Fingscheidt:
Relaxed Attention: A Simple Method to Boost Performance of End-to-End Automatic Speech Recognition. CoRR abs/2107.01275 (2021) - 2020
- [c9]Jan Baumann, Timo Lohrenz, Alexander Roy, Tim Fingscheidt:
Beyond the Dcase 2017 Challenge on Rare Sound Event Detection: A Proposal for a More Realistic Training and Test Framework. ICASSP 2020: 611-615 - [c8]Timo Lohrenz, Tim Fingscheidt:
BLSTM-Driven Stream Fusion for Automatic Speech Recognition: Novel Methods and a Multi-Size Window Fusion Example. INTERSPEECH 2020: 26-30
2010 – 2019
- 2019
- [c7]Timo Lohrenz, Maximilian Strake, Tim Fingscheidt:
On Temporal Context Information for Hybrid BLSTM-Based Phoneme Recognition. ASRU 2019: 516-523 - 2018
- [c6]Timo Lohrenz, Wei Li, Tim Fingscheidt:
DNN/CNN Acoustic Model Turbo Fusion for Phoneme Recognition. ITG Symposium on Speech Communication 2018: 1-5 - [c5]Maximilian Strake, Pascal Behr, Timo Lohrenz, Tim Fingscheidt:
Densenet Blstm for Acoustic Modeling in Robust ASR. SLT 2018: 6-12 - [c4]Timo Lohrenz, Wei Li, Tim Fingscheidt:
A New Timit Benchmark for Context-Independent Phone Recognition Using Turbo Fusion. SLT 2018: 498-505 - 2017
- [c3]Timo Lohrenz, Tim Fingscheidt:
Turbo fusion of magnitude and phase information for DNN-based phoneme recognition. ASRU 2017: 118-125 - 2016
- [c2]Timo Lohrenz, Simon Receveur, Tim Fingscheidt:
EXIT Charts for Turbo Automatic Speech Recognition: A Case Study. ITG Symposium on Speech Communication 2016: 1-5 - [c1]Simon Receveur, Timo Lohrenz, Tim Fingscheidt:
Introducing Block-Wise Processing into Turbo Viterbi ASR. ITG Symposium on Speech Communication 2016: 1-5
Coauthor Index
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