AUTOMATIC SPEECH RECOGNITION-SPEECH TO TEXT CONVERSION USING PYTHON LIBRARIES

AUTOMATIC SPEECH RECOGNITION-SPEECH TO TEXT CONVERSION USING PYTHON LIBRARIES

1)Gaurav Tripathi 2) N Sohan Mani 3) L.Sharath Chandra 4) B.Soumya Sree 5) B.Soumya 6) P.Soumya

Assistant Professor Sai Teja

Head of  Department  Dr.Thayaba khatoon

 Department of Artificial Intelligence and Machine Learning (AI&ML)

Malla Reddy University, Maisammaguda, Hyderabad

 ABSTRACT

Automatic Speech Recognition (ASR) has been a subject of extensive research in recent years due to its potential applications in various domains such as human-computer interaction, transcription services, voice-controlled systems, and accessibility tools. This abstract focuses on the research perspective of Automatic Speech Recognition websites, which serve as platforms for deploying and evaluating ASR algorithms and methodologies. ASR websites provide researchers with a valuable resource for testing and benchmarking their ASR models and techniques. These platforms offer a standardized interface and a diverse range of speech datasets, enabling researchers to compare and evaluate the performance of different ASR systems under various conditions. The availability of such websites facilitates fair and systematic evaluations, leading to advancements in ASR algorithms and approaches.

Keywords—Automatic Speech Recognition, ASR, extensive research, potential applications, domains, human-computer interaction, transcription services, voice-controlled systems, accessibility tools, research perspective, Automatic Speech Recognition websites, platforms, deploying, evaluating, ASR algorithms, methodologies.