Punctuation restoration for speech transcripts using large language models
This thesis explores punctuation restoration in speech transcripts using Large Language Models (LLMs) to enhance text readability and comprehension. We focus on the efficacy of LLMs, specifically XLM-RoBERTa and Llama-2. The primary contributions include the refinement of the existing XLM-RoBERTa mo...
Saved in:
Main Author: | Liu, Changsong |
---|---|
Other Authors: | Chng Eng Siong |
Format: | Final Year Project |
Language: | English |
Published: |
Nanyang Technological University
2024
|
Subjects: | |
Online Access: | https://hdl.handle.net/10356/175306 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Institution: | Nanyang Technological University |
Language: | English |
Similar Items
-
Model-driven smart contract generation leveraging pretrained large language models
by: Jiang, Qinbo
Published: (2024) -
基于2011 版新标准的标点符号用法研究 = New Standard Based on 2011 Usage of Punctuation
by: 丁菁, et al.
Published: (2011) -
THESIS TITLE: ADVANCES IN PUNCTUATION AND DISFLUENCY PREDICTION
by: WANG XUANCONG
Published: (2015) -
An efficient transformer-based model for Vietnamese punctuation prediction
by: TRAN, Hieu, et al.
Published: (2021) -
Leveraging large language models for effective user interaction via conversations
by: Zhang, Mengao
Published: (2024)