74 citations · 98 across the 6 of their papers we have counts for
7 papers
Multi-View Frequency-Attention Alternative to CNN Frontends for Automatic Speech Recognition
Belen Alastruey, Lukas Drude, Jahn Heymann +1
Convolutional frontends are a typical choice for Transformer-based automatic speech recognition to preprocess the spectrogram, reduce its sequence length, and combine local informa…
Multi-channel Opus compression for far-field automatic speech recognition with a fixed bitrate budget
Lukas Drude, Jahn Heymann, Andreas Schwarz +1
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. Howev…
Far-Field Automatic Speech Recognition
Reinhold Haeb-Umbach, Jahn Heymann, Lukas Drude +3
The machine recognition of speech spoken at a distance from the microphones, known as far-field automatic speech recognition (ASR), has received a significant increase of attention…
Subword Regularization: An Analysis of Scalability and Generalization for End-to-End Automatic Speech Recognition
Egor Lakomkin, Jahn Heymann, Ilya Sklyar +1
Subwords are the most widely used output units in end-to-end speech recognition. They combine the best of two worlds by modeling the majority of frequent words directly and at the…
Unsupervised training of neural mask-based beamforming
Lukas Drude, Jahn Heymann, Reinhold Haeb-Umbach
We present an unsupervised training approach for a neural network-based mask estimator in an acoustic beamforming application. The network is trained to maximize a likelihood crite…
ESPnet: End-to-End Speech Processing Toolkit
Shinji Watanabe, Takaaki Hori, Shigeki Karita +9
This paper introduces a new open source platform for end-to-end speech processing named ESPnet. ESPnet mainly focuses on end-to-end automatic speech recognition (ASR), and adopts w…