Methods for Punctuation Restoration in Automatic Speech Recognition Systems

Sobirova Zarnigor Ganijon kizi

doi:10.51699/cajlpc.v7i3.1546

Authors

Sobirova Zarnigor Ganijon kizi Computational Linguistics and Digital Technologies, Tashkent State University of Uzbek Language and Literature

DOI:

https://doi.org/10.51699/cajlpc.v7i3.1546

Keywords:

Punctuation Restoration, Automatic Speech Recognition, ASR, Speech Recognition, Speech Transcripts, Uzbpunct Dataset

Abstract

Punctuation restoration constitutes one of the most significant Natural Language Processing (NLP) tasks within Automatic Speech Recognition (ASR) systems. Automatic Speech Recognition refers to a computational technology that enables machines to recognize, process, and transcribe human speech into textual form. ASR systems serve as a fundamental component in numerous NLP applications, including intelligent voice assistants, automated call-center systems, speech analytics, and machine translation technologies. With the exponential growth of digital content and spoken communication platforms, ASR technologies have become an indispensable element of modern intelligent information systems and services.

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