When Large Language Models Meet Speech: A Survey on Integration Approaches

Recent advancements in large language models (LLMs) have spurred interest in expanding their application beyond text-based tasks.A large number of studies have explored integrating other modalities with LLMs, notably speech modality, which is naturally related to text.This paper surveys the integration of speech with LLMs, categorizing the methodologies into three primary approaches: textbased, latent-representation-based, and audiotoken-based integration.We also demonstrate how these methods are applied across various speech-related applications and highlight the challenges in this field to offer inspiration for future research.

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Published
2025-01-01
DOI
https://doi.org/10.18653/v1/2025.findings-acl.1041
Primary Topic
Natural Language Processing Techniques
Type
article
Field-Weighted Citation Impact
0.00

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article

When Large Language Models Meet Speech: A Survey on Integration Approaches

Yahan Yu, Shuichiro Shimizu, Chenhui Chu, Zhengdong Yang
Natural Language Processing Techniques
article

When Large Language Models Meet Speech: A Survey on Integration Approaches

Yahan Yu, Shuichiro Shimizu, Chenhui Chu, Zhengdong Yang
article en

Abstract

Recent advancements in large language models (LLMs) have spurred interest in expanding their application beyond text-based tasks.A large number of studies have explored integrating other modalities with LLMs, notably speech modality, which is naturally related to text.This paper surveys the integration of speech with LLMs, categorizing the methodologies into three primary approaches: textbased, latent-representation-based, and audiotoken-based integration.We also demonstrate how these methods are applied across various speech-related applications and highlight the challenges in this field to offer inspiration for future research.

Kyoto University (JP)
Japan Society for the Promotion of Science
Reduced inequalities
Openalex Percentile: Top 90%
Natural Language Processing Techniques
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