Detail publikace
Speculative Speech Recognition by Audio-Prefixed Low-Rank Adaptation of Language Models
YUSUF, B. BASKAR, M. ROSENBERG, A. RAMABHADRAN, B.
Originální název
Speculative Speech Recognition by Audio-Prefixed Low-Rank Adaptation of Language Models
Typ
článek ve sborníku ve WoS nebo Scopus
Jazyk
angličtina
Originální abstrakt
This paper explores speculative speech recognition (SSR), where we empower conventional automatic speech recognition (ASR) with speculation capabilities, allowing the recognizer to run ahead of audio. We introduce a metric for measuring SSR performance and we propose a model which does SSR by com bining a RNN-Transducer-based ASR system with an audioprefixed language model (LM). The ASR system transcribes ongoing audio and feeds the resulting transcripts, along with an audiodependent prefix, to the LM, which speculates likely completions for the transcriptions. We experiment with a variety of ASR datasets on which show the efficacy our method and the feasibility of SSR as a method of reducing ASR latency.
Klíčová slova
low-latency speech recognition, speculative speech recognition, prefix language model, low-rank adaptation
Autoři
YUSUF, B.; BASKAR, M.; ROSENBERG, A.; RAMABHADRAN, B.
Vydáno
1. 9. 2024
Nakladatel
International Speech Communication Association
Místo
Kos
ISSN
1990-9772
Periodikum
Proceedings of Interspeech
Ročník
2024
Číslo
9
Stát
Francouzská republika
Strany od
792
Strany do
796
Strany počet
5
URL
BibTex
@inproceedings{BUT193739,
author="YUSUF, B. and BASKAR, M. and ROSENBERG, A. and RAMABHADRAN, B.",
title="Speculative Speech Recognition by Audio-Prefixed Low-Rank Adaptation of Language Models",
booktitle="Proceedings of Interspeech 2024",
year="2024",
journal="Proceedings of Interspeech",
volume="2024",
number="9",
pages="792--796",
publisher="International Speech Communication Association",
address="Kos",
doi="10.21437/Interspeech.2024-298",
issn="1990-9772",
url="https://www.isca-archive.org/interspeech_2024/yusuf24_interspeech.pdf"
}
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