• Pallavi Meshram
• Vijaya Kamble
• Aditya Waghmare
• Sagar Nimkar
• Ashwini Tarware

The internet has undergone changes over time, transforming numerous fields and impacting countless lives. It has brought significant benefits to humanity, particularly in the area of communication. Thanks to the internet, communication has become faster and more convenient. The purpose of this research is to investigate various methodologies for converting speech to text and text to speech, which will be employed in a voice-based email system that utilizes interactive voice response technology. The study aims to compare different techniques used for these conversions and identify the most efficient one that can be applied to both processes. The review of the literature reveals that the Hidden Markov Model (HMM) is a statistical model that is the most appropriate for both speech-to-text and text-to-speech conversions. Finally, we propose a model that employs HMM and Artificial Neural Network (ANN) methods for speech-to-text conversions, and HMM for text-to-speech conversions. Our team devised an idea of utilizing speech recognition technology to convert spoken language into text and display it on an electronic board. The primary purpose of this display system is to present day-to-day information in real-time or at regular intervals to colleges and universities. Being a wireless system, it can display breaking news or announcements more efficiently than traditional notice boards. The display board is designed to show text generated from speech using a Wi-Fi module that enables communication, and the speech-to-text conversion is facilitated by Python Libraries. Overall, the proposed system is an innovative solution that leverages speech recognition and wireless technology to enhance the communication of information in academic institutions.

text-to-speech conversion, HMM, ANN, Notice Board

"Voice to Text Based Noticeboard with Integrated Android Application", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.10, Issue 4, page no.l340-l346, April-2023, Available :http://www.jetir.org/papers/JETIR2304B51.pdf

"Voice to Text Based Noticeboard with Integrated Android Application", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.10, Issue 4, page no. ppl340-l346, April-2023, Available at : http://www.jetir.org/papers/JETIR2304B51.pdf