14 citations · 15 across the 5 of their papers we have counts for
5 papers
Investigating Decoder-only Large Language Models for Speech-to-text Translation
Chao-Wei Huang, Hui Lu, Hongyu Gong +4
Large language models (LLMs), known for their exceptional reasoning capabilities, generalizability, and fluency across diverse domains, present a promising avenue for enhancing spe…
MMM: Multi-Layer Multi-Residual Multi-Stream Discrete Speech Representation from Self-supervised Learning Model
Jiatong Shi, Xutai Ma, Hirofumi Inaguma +2
Speech discrete representation has proven effective in various downstream applications due to its superior compression rate of the waveform, fast convergence during training, and c…
SeamlessM4T: Massively Multilingual & Multimodal Machine Translation
Seamless Communication, Loïc Barrault, Yu-An Chung +65
What does it take to create the Babel Fish, a tool that can help individuals translate speech between any two languages? While recent breakthroughs in text-based models have pushed…
Hybrid Transducer and Attention based Encoder-Decoder Modeling for Speech-to-Text Tasks
Yun Tang, Anna Y. Sun, Hirofumi Inaguma +5
Transducer and Attention based Encoder-Decoder (AED) are two widely used frameworks for speech-to-text tasks. They are designed for different purposes and each has its own benefits…
Enhancing Speech-to-Speech Translation with Multiple TTS Targets
Jiatong Shi, Yun Tang, Ann Lee +4
It has been known that direct speech-to-speech translation (S2ST) models usually suffer from the data scarcity issue because of the limited existing parallel materials for both sou…