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20132025
most citedBigSSL: Exploring the Frontier of Large-Scale Semi-Supervised Learning for Automatic Speech Recognition

164 citations · 535 across the 44 of their papers we have counts for

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Showing 2024Show all

9 papers · 1 filter

cs.CL2024

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…

eess.AS2024

Zero-shot Cross-lingual Voice Transfer for TTS

Fadi Biadsy, Youzheng Chen, Isaac Elias +4

In this paper, we introduce a zero-shot Voice Transfer (VT) module that can be seamlessly integrated into a multi-lingual Text-to-speech (TTS) system to transfer an individual's vo…

cs.CL2024

STAB: Speech Tokenizer Assessment Benchmark

Shikhar Vashishth, Harman Singh, Shikhar Bharadwaj +6

Representing speech as discrete tokens provides a framework for transforming speech into a format that closely resembles text, thus enabling the use of speech as an input to the wi…

eess.AS2024

Speculative Speech Recognition by Audio-Prefixed Low-Rank Adaptation of Language Models

Bolaji Yusuf, Murali Karthick Baskar, Andrew Rosenberg +1

This paper explores speculative speech recognition (SSR), where we empower conventional automatic speech recognition (ASR) with speculation capabilities, allowing the recognizer to…

cs.AI2024

Speech Prefix-Tuning with RNNT Loss for Improving LLM Predictions

Murali Karthick Baskar, Andrew Rosenberg, Bhuvana Ramabhadran +2

In this paper, we focus on addressing the constraints faced when applying LLMs to ASR. Recent works utilize prefixLM-type models, which directly apply speech as a prefix to LLMs fo…

eess.AS2024★ 1 cited

ASTRA: Aligning Speech and Text Representations for Asr without Sampling

Neeraj Gaur, Rohan Agrawal, Gary Wang +3

This paper introduces ASTRA, a novel method for improving Automatic Speech Recognition (ASR) through text injection.Unlike prevailing techniques, ASTRA eliminates the need for samp…