4 citations · 5 across the 8 of their papers we have counts for
8 papers
Schema Augmentation for Zero-Shot Domain Adaptation in Dialogue State Tracking
Christopher Richardson, Roshan Sharma, Neeraj Gaur +3
Zero-shot domain adaptation for dialogue state tracking (DST) remains a challenging problem in task-oriented dialogue (TOD) systems, where models must generalize to target domains…
Speech vs. Transcript: Does It Matter for Human Annotators in Speech Summarization?
Roshan Sharma, Suwon Shon, Mark Lindsey +3
Reference summaries for abstractive speech summarization require human annotation, which can be performed by listening to an audio recording or by reading textual transcripts of th…
On the Evaluation of Speech Foundation Models for Spoken Language Understanding
Siddhant Arora, Ankita Pasad, Chung-Ming Chien +9
The Spoken Language Understanding Evaluation (SLUE) suite of benchmark tasks was recently introduced to address the need for open resources and benchmarking of complex spoken langu…
AugSumm: towards generalizable speech summarization using synthetic labels from large language model
Jee-weon Jung, Roshan Sharma, William Chen +2
Abstractive speech summarization (SSUM) aims to generate human-like summaries from speech. Given variations in information captured and phrasing, recordings can be summarized in mu…
LoFT: Local Proxy Fine-tuning For Improving Transferability Of Adversarial Attacks Against Large Language Model
Muhammad Ahmed Shah, Roshan Sharma, Hira Dhamyal +10
It has been shown that Large Language Model (LLM) alignments can be circumvented by appending specially crafted attack suffixes with harmful queries to elicit harmful responses. To…
UniverSLU: Universal Spoken Language Understanding for Diverse Tasks with Natural Language Instructions
Siddhant Arora, Hayato Futami, Jee-weon Jung +6
Recent studies leverage large language models with multi-tasking capabilities, using natural language prompts to guide the model's behavior and surpassing performance of task-speci…
Evaluating Speech Synthesis by Training Recognizers on Synthetic Speech
Dareen Alharthi, Roshan Sharma, Hira Dhamyal +3
Modern speech synthesis systems have improved significantly, with synthetic speech being indistinguishable from real speech. However, efficient and holistic evaluation of synthetic…
Augmenting text for spoken language understanding with Large Language Models
Roshan Sharma, Suyoun Kim, Daniel Lazar +7
Spoken semantic parsing (SSP) involves generating machine-comprehensible parses from input speech. Training robust models for existing application domains represented in training d…