Implementation of Number Transcription Tool

The creation of a precise speech-based number transcription tool that accurately transforms spoken numbers (0–9) into their corresponding digits on a screen has become extremely important in today's digital world. In order to accomplish error-free and reliable transcription of numerical data, a system using advanced speech recognition technologies was designed and implemented, as revealed by this paper. The system uses a combination of machine learning models that have been combined and trained on large datasets to provide greater transcription accuracy and adaptability to different speech patterns. This paper thoroughly explains the system's technological architecture, highlighting its features and functionalities, with particular emphasis on its capacity to convert spoken numbers into their corresponding numerical representations on a visual interface. The paper also consists of a table which provides a brief summary of the benefits and drawbacks of several models for automatic speech recognition number transcription including hybrid DNN-HMM systems, noise-robust techniques, LAS models and a comparison of our system with these existing systems. The various applications of this system include finance, telecommunications, and data entry, where precise number transcription is of utmost importance.