648 citations · 4k across the 58 of their papers we have counts for
61 papers
Improving speaker verification robustness with synthetic emotional utterances
Nikhil Kumar Koditala, Chelsea Jui-Ting Ju, Ruirui Li +3
A speaker verification (SV) system offers an authentication service designed to confirm whether a given speech sample originates from a specific speaker. This technology has paved…
Large Language Model Based Generative Error Correction: A Challenge and Baselines for Speech Recognition, Speaker Tagging, and Emotion Recognition
Chao-Han Huck Yang, Taejin Park, Yuan Gong +18
Given recent advances in generative AI technology, a key question is how large language models (LLMs) can enhance acoustic modeling tasks using text decoding results from a frozen,…
Turn-taking and Backchannel Prediction with Acoustic and Large Language Model Fusion
Jinhan Wang, Long Chen, Aparna Khare +6
We propose an approach for continuous prediction of turn-taking and backchanneling locations in spoken dialogue by fusing a neural acoustic model with a large language model (LLM).…
Post-Training Embedding Alignment for Decoupling Enrollment and Runtime Speaker Recognition Models
Chenyang Gao, Brecht Desplanques, Chelsea J. -T. Ju +2
Automated speaker identification (SID) is a crucial step for the personalization of a wide range of speech-enabled services. Typical SID systems use a symmetric enrollment-verifica…
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…