2 papers
eess.AS2024
Contextualization of ASR with LLM using phonetic retrieval-based augmentation
Zhihong Lei, Xingyu Na, Mingbin Xu +5
Large language models (LLMs) have shown superb capability of modeling multimodal signals including audio and text, allowing the model to generate spoken or textual response given a…
eess.AS2024
Retrieval Augmented Correction of Named Entity Speech Recognition Errors
Ernest Pusateri, Anmol Walia, Anirudh Kashi +6
In recent years, end-to-end automatic speech recognition (ASR) systems have proven themselves remarkably accurate and performant, but these systems still have a significant error r…