Flask-based ASR for Automated Disorder Speech Recognition

Abstract

Speech disorders encompass a diverse range of conditions hindering effective communication, stemming from developmental, neurological, or physical factors. These challenges impact daily life and opportunities. Automatic Speech Recognition (ASR) technology emerges as a pivotal solution. ASR, powered by sophisticated algorithms, transcribes spoken language into written text, transcending traditional communication barriers. Tailorable to accommodate unique speech disorders, ASR offers the promise of empowering individuals to articulate their thoughts. Our Python Flask-based ASR(FBASR) applications meticulously crafted to cater to individuals, including children, grappling with speech disorders. It provides a user-friendly platform. Users simply submit a speech audio file in WAV format, and the application transcribes it. Alongside recognized text, it furnishes vital audio metrics. Additionally, it generates visual audio signal and spectrogram representations, all stored efficiently for future reference. The application's profound advantage lies in granting a voice to individuals with speech disorders, facilitating education, employment, and healthcare interactions. Furthermore, it serves as a resource for research and therapy development, promising inclusivity and enriching lives. The proposed work concludes by discussing the future outlook of cloud-based ASR and identifying some of the key areas of research that need to be addressed to make cloud-based DSR systems more accurate, reliable, and accessible.