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Efficient One-to-Many Translation with Joint Multi-Stream Diffusion
Yiwen Guan, Jacob Whitehill
One-to-many machine translation (MT) is computationally expensive for autoregressive (AR) systems, which suffer from linear latency scaling with both sequence length and the number…
Learning to Translate from Soft to Hard LLM Prompts
Pitipat Kongsomjit, Suryansh Goyal, Jacob Whitehill
Soft prompting, also known as continuous prompting, is a parameter-efficient method for tuning LLMs to specific tasks. Like other machine learning techniques, its parameters encode…
Interactive In-Meeting Speaker Correction with Human Feedback
Xinlu He, Yiwen Guan, Badrivishal Paurana +3
Most automatic speech processing systems operate in ``open loop'' mode without user feedback about who said what, yet human-in-the-loop workflows can potentially enable higher accu…
Transformer-Encoder Trees for Efficient Multilingual Machine Translation and Speech Translation
Yiwen Guan, Jacob Whitehill
Multilingual translation suffers from computational redundancy, especially when translating into multiple languages simultaneously. In addition, translation quality can suffer for…
Improving Speech Recognition of Named Entities in Classroom Speech with LLM Revision and Phonetic-Semantic Context
Viet Anh Trinh, Xinlu He, Jacob Whitehill
Classroom speech and lectures often contain named entities (NEs) such as names of people and special terminology. While automatic speech recognition (ASR) systems have achieved rem…
Survey of End-to-End Multi-Speaker Automatic Speech Recognition for Monaural Audio
Xinlu He, Jacob Whitehill
Monaural multi-speaker automatic speech recognition (ASR) remains challenging due to data scarcity and the intrinsic difficulty of recognizing and attributing words to individual s…