23 citations · 39 across the 10 of their papers we have counts for
10 papers
Rethinking Language Model-Based Generative Speech Enhancement in the Latent Space of a Neural Audio Codec
Yihui Fu, Zhengyang Li, Tim Fingscheidt
Language model (LM)-based speech enhancement (SE) has recently emerged rapidly using latent space features of neural audio codecs (NACs). In this paper, first, we present a unified…
Noise-Robust AV-ASR Using Visual Features Both in the Whisper Encoder and Decoder
Zhengyang Li, Thomas Graave, Björn Möller +3
In audiovisual automatic speech recognition (AV-ASR) systems, information fusion of visual features in a pre-trained ASR has been proven as a promising method to improve noise robu…
OpenViGA: Video Generation for Automotive Driving Scenes by Streamlining and Fine-Tuning Open Source Models with Public Data
Björn Möller, Zhengyang Li, Malte Stelzer +4
Recent successful video generation systems that predict and create realistic automotive driving scenes from short video inputs assign tokenization, future state prediction (world m…
Relaxed Attention for Transformer Models
Timo Lohrenz, Björn Möller, Zhengyang Li +1
The powerful modeling capabilities of all-attention-based transformer architectures often cause overfitting and - for natural language processing tasks - lead to an implicitly lear…
Bandwidth-Scalable Fully Mask-Based Deep FCRN Acoustic Echo Cancellation and Postfiltering
Ernst Seidel, Rasmus Kongsgaard Olsson, Karim Haddad +3
Although today's speech communication systems support various bandwidths from narrowband to super-wideband and beyond, state-of-the art DNN methods for acoustic echo cancellation (…
The Quadratic Wasserstein Metric With Squaring Scaling For Seismic Velocity Inversion
Zhengyang Li, Yijia Tang, Jing Chen +1
The quadratic Wasserstein metric has shown its power in measuring the difference between probability densities, which benefits optimization objective function with better convexity…
Relaxed Attention: A Simple Method to Boost Performance of End-to-End Automatic Speech Recognition
Timo Lohrenz, Patrick Schwarz, Zhengyang Li +1
Recently, attention-based encoder-decoder (AED) models have shown high performance for end-to-end automatic speech recognition (ASR) across several tasks. Addressing overconfidence…
Multi-Encoder Learning and Stream Fusion for Transformer-Based End-to-End Automatic Speech Recognition
Timo Lohrenz, Zhengyang Li, Tim Fingscheidt
Stream fusion, also known as system combination, is a common technique in automatic speech recognition for traditional hybrid hidden Markov model approaches, yet mostly unexplored…
Point Spread Function Estimation for Wide Field Small Aperture Telescopes with Deep Neural Networks and Calibration Data
Peng Jia, Xuebo Wu, Zhengyang Li +4
The point spread function (PSF) reflects states of a telescope and plays an important role in development of data processing methods, such as PSF based astrometry, photometry and i…
Point Spread Function Modelling for Wide Field Small Aperture Telescopes with a Denoising Autoencoder
Peng Jia, Xiyu Li, Zhengyang Li +2
The point spread function reflects the state of an optical telescope and it is important for data post-processing methods design. For wide field small aperture telescopes, the poin…