Search Results for author: Jahn Heymann

Found 5 papers, 1 papers with code

Multi-View Frequency-Attention Alternative to CNN Frontends for Automatic Speech Recognition

no code implementations12 Jun 2023 Belen Alastruey, Lukas Drude, Jahn Heymann, Simon Wiesler

Convolutional frontends are a typical choice for Transformer-based automatic speech recognition to preprocess the spectrogram, reduce its sequence length, and combine local information in time and frequency similarly.

Automatic Speech Recognition speech-recognition +1

Multi-channel Opus compression for far-field automatic speech recognition with a fixed bitrate budget

no code implementations15 Jun 2021 Lukas Drude, Jahn Heymann, Andreas Schwarz, Jean-Marc Valin

Automatic speech recognition (ASR) in the cloud allows the use of larger models and more powerful multi-channel signal processing front-ends compared to on-device processing.

Automatic Speech Recognition Automatic Speech Recognition (ASR) +1

Unsupervised training of neural mask-based beamforming

no code implementations2 Apr 2019 Lukas Drude, Jahn Heymann, Reinhold Haeb-Umbach

In contrast to previous work on unsupervised training of neural mask estimators, our approach avoids the need for a possibly pre-trained teacher model entirely.

speech-recognition Speech Recognition

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