A multi-threaded approach for improved and faster accent transcription of chemical terms

Abstract

The proposed research aims to improve real-time transcription of English accents by focusing on transcribing technical terms related to chemistry using an innovative framework that blends multi-threading and asynchronous programming techniques for enhanced speed and accuracy. The method lays the groundwork for real-time transcription by taking into account the nuances of regional accents. Highlighting the significance of embracing language and cultural diversity underscores the importance of advancements in speech-to-text technologies. Continuous learning mechanisms and adaptive language models serve to enhance the quality of transcription. Ensuring performance in time is guaranteed through the use of scalable infrastructure while maintaining operational efficiency through ongoing evaluation and enhancement processes. This innovative approach not only enhances transcription precision but also establishes a system that appreciates and embraces the diverse range of linguistic nuances present in Indian English accents, promoting the development of inclusive and effective communication technologies.

This paper presents a comprehensive framework

• for real-time transcription of English speech in the rich tapestry of regional Indian accents, with a distinctive focus on the intricate classification of chemical terms;

• to navigate through the unique linguistic landscapes, addressing the challenges posed by the diverse accents prevalent across various Indian regions;

• to emphasize the nuanced identification and categorization of chemical terminology within the transcribed content.