1.9k citations · 3.5k across the 108 of their papers we have counts for
8 papers · 2 filters
Token-Level Serialized Output Training for Joint Streaming ASR and ST Leveraging Textual Alignments
Sara Papi, Peidong Wang, Junkun Chen +3
In real-world applications, users often require both translations and transcriptions of speech to enhance their comprehension, particularly in streaming scenarios where incremental…
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…
Speak Foreign Languages with Your Own Voice: Cross-Lingual Neural Codec Language Modeling
Ziqiang Zhang, Long Zhou, Chengyi Wang +10
We propose a cross-lingual neural codec language model, VALL-E X, for cross-lingual speech synthesis. Specifically, we extend VALL-E and train a multi-lingual conditional codec lan…