Search Results for author:
Found 3 papers, 2 papers with code
A unified multichannel far-field speech recognition system: combining neural beamforming with attention based end-to-end model
Far-field speech recognition is a challenging task that conventionally uses signal processing beamforming to attack noise and interference problem.
V2A-Mapper: A Lightweight Solution for Vision-to-Audio Generation by Connecting Foundation Models
In this paper, we propose a lightweight solution to this problem by leveraging foundation models, specifically CLIP, CLAP, and AudioLDM.
A low latency attention module for streaming self-supervised speech representation learning
The SA represents our proposal for an efficient streaming SSRL implementation, while the LLSA solves the latency build-up problem of other streaming attention architectures, such as the masked acausal attention (MAA), guaranteeing a latency equal to one layer even when multiple layers are stacked.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+3
