• Mr. P.Muthyalu
• D.Subhash

The project "Recognizing Speech Emotions Using Voice and Text" endeavors to create a robust and versatile system that can discern the emotional nuances embedded within both spoken words and written text. Emotions play a pivotal role in human communication, influencing the effectiveness and depth of interactions. By harnessing cutting-edge technologies in machine learning and signal processing, this project aims to develop algorithms capable of extracting and analyzing various features from voice recordings and textual data to accurately classify the emotional states of speakers.The system will employ sophisticated techniques such as sentiment analysis, prosody analysis, and deep learning models to capture subtle cues indicative of different emotional states, including joy, sadness, anger, fear, and more. Through extensive training on diverse datasets encompassing a wide range of languages, dialects, and cultural contexts, the system will learn to generalize its understanding of emotional expressions, thereby ensuring robust performance across different demographics and scenarios.Ultimately, the envisioned application of this technology spans across multiple domains, including customer service, healthcare, education, and entertainment. By enabling devices and applications to perceive and respond to human emotions more effectively, the project seeks to enhance user experiences, foster empathy-driven interactions, and facilitate deeper connections in an increasingly digital world

Recognise Speech Emotions Using Voice And Text

"Recognise Speech Emotions Using Voice And Text ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.11, Issue 6, page no.381-383, June-2024, Available :http://www.jetir.org/papers/JETIRGL06064.pdf

"Recognise Speech Emotions Using Voice And Text ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.11, Issue 6, page no. pp381-383, June-2024, Available at : http://www.jetir.org/papers/JETIRGL06064.pdf