A Logical Model for Recognizing Sentences with Punctuation using Python API

In converting spoken language to text., there are challenges such as fluency and pronunciation variation. This study incorporated advanced speech-to-text and summarization techniques using the Python API Natural Language Toolkit (NLTK). The proposed model refines custom punctuation handling and text conversion from continuous audio. It was found that the proposed model recognized sentences quickly and accurately during the experiment, and the results were tabulated.

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Publication Details

Published
2024-12-17
DOI
https://doi.org/10.1109/icicnis64247.2024.10823228
Primary Topic
Natural Language Processing Techniques
Type
article
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article

A Logical Model for Recognizing Sentences with Punctuation using Python API

K Rajchandar, Aparna Chiguru
Natural Language Processing Techniques
article

A Logical Model for Recognizing Sentences with Punctuation using Python API

K Rajchandar, Aparna Chiguru
article en

Abstract

In converting spoken language to text., there are challenges such as fluency and pronunciation variation. This study incorporated advanced speech-to-text and summarization techniques using the Python API Natural Language Toolkit (NLTK). The proposed model refines custom punctuation handling and text conversion from continuous audio. It was found that the proposed model recognized sentences quickly and accurately during the experiment, and the results were tabulated.

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Natural Language Processing Techniques
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A Logical Model for Recognizing Sentences with Punctuation using Python API — K Rajchandar, Aparna Chiguru · (2024) | TGRS Research Map | TGRS