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Xingyu Na

2 accepted papers

2025

Contextualization of ASR with LLM using phonetic retrieval-based augmentation

ICASSP 2025accepted

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 speech input. However, it remains a challenge for the model to recognize personal named entities, such as contacts in a…

Cited by 0Source ↗Scholar ↗
2016

An empirical exploration of CTC acoustic models

ICASSP 2016accepted

The connectionist temporal classification (CTC) loss function has several interesting properties relevant for automatic speech recognition (ASR): applied on top of deep recurrent neural networks (RNNs), CTC learns the alignments between speech frames and label sequences automatically, which removes…

Cited by 0Source ↗Scholar ↗