53 citations · 151 across the 26 of their papers we have counts for
6 papers · 1 filter
Align-SLM: Textless Spoken Language Models with Reinforcement Learning from AI Feedback
Guan-Ting Lin, Prashanth Gurunath Shivakumar, Aditya Gourav +4
While textless Spoken Language Models (SLMs) have shown potential in end-to-end speech-to-speech modeling, they still lag behind text-based Large Language Models (LLMs) in terms of…
Speech Recognition Rescoring with Large Speech-Text Foundation Models
Prashanth Gurunath Shivakumar, Jari Kolehmainen, Aditya Gourav +4
Large language models (LLM) have demonstrated the ability to understand human language by leveraging large amount of text data. Automatic speech recognition (ASR) systems are often…
Multi-Modal Retrieval For Large Language Model Based Speech Recognition
Jari Kolehmainen, Aditya Gourav, Prashanth Gurunath Shivakumar +5
Retrieval is a widely adopted approach for improving language models leveraging external information. As the field moves towards multi-modal large language models, it is important…
Investigating Training Strategies and Model Robustness of Low-Rank Adaptation for Language Modeling in Speech Recognition
Yu Yu, Chao-Han Huck Yang, Tuan Dinh +10
The use of low-rank adaptation (LoRA) with frozen pretrained language models (PLMs) has become increasing popular as a mainstream, resource-efficient modeling approach for memory-c…
Paralinguistics-Enhanced Large Language Modeling of Spoken Dialogue
Guan-Ting Lin, Prashanth Gurunath Shivakumar, Ankur Gandhe +6
Large Language Models (LLMs) have demonstrated superior abilities in tasks such as chatting, reasoning, and question-answering. However, standard LLMs may ignore crucial paralingui…
Towards ASR Robust Spoken Language Understanding Through In-Context Learning With Word Confusion Networks
Kevin Everson, Yile Gu, Huck Yang +10
In the realm of spoken language understanding (SLU), numerous natural language understanding (NLU) methodologies have been adapted by supplying large language models (LLMs) with tr…