1.9k citations · 2.8k across the 43 of their papers we have counts for
5 papers · 2 filters
Accelerating Transducers through Adjacent Token Merging
Yuang Li, Yu Wu, Jinyu Li +1
Recent end-to-end automatic speech recognition (ASR) systems often utilize a Transformer-based acoustic encoder that generates embedding at a high frame rate. However, this design…
Prompting Large Language Models for Zero-Shot Domain Adaptation in Speech Recognition
Yuang Li, Yu Wu, Jinyu Li +1
The integration of Language Models (LMs) has proven to be an effective way to address domain shifts in speech recognition. However, these approaches usually require a significant a…
Accurate and Structured Pruning for Efficient Automatic Speech Recognition
Huiqiang Jiang, Li Lyna Zhang, Yuang Li +7
Automatic Speech Recognition (ASR) has seen remarkable advancements with deep neural networks, such as Transformer and Conformer. However, these models typically have large model s…
VioLA: Unified Codec Language Models for Speech Recognition, Synthesis, and Translation
Tianrui Wang, Long Zhou, Ziqiang Zhang +6
Recent research shows a big convergence in model architecture, training objectives, and inference methods across various tasks for different modalities. In this paper, we propose V…
Neural Codec Language Models are Zero-Shot Text to Speech Synthesizers
Chengyi Wang, Sanyuan Chen, Yu Wu +10
We introduce a language modeling approach for text to speech synthesis (TTS). Specifically, we train a neural codec language model (called Vall-E) using discrete codes derived from…