Harnessing pre-trained LLMs to improve ASR systems, particularly for low-resource
languages, is now an emerging area of research. Existing methods range from using LLMs …

The success of large language models (LLMs) has prompted efforts to integrate speech and
audio data, aiming to create general foundation models capable of processing both textual …

Large language models (LLMs) can adapt to new tasks through in-context learning (ICL)
based on a few examples presented in dialogue history without any model parameter …

Large audio-language models (LALMs) enhance traditional large language models by
integrating audio perception capabilities, allowing them to tackle audio-related tasks …

Following the remarkable success of Large Language Models (LLMs) in NLP tasks, there is
increasing interest in extending their capabilities to speech--the most common form in …