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@article{157785,
        author = {Dr. Shivani Dubey and Siddharth Singh and Sonali Kumari and Sunny and Dr. Ajay Kumar Sahu},
        title = {Implementation of Virtual Voice Assistant in collaboration of Emotion Detector},
        journal = {International Journal of Innovative Research in Technology},
        year = {},
        volume = {9},
        number = {8},
        pages = {51-57},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=157785},
        abstract = {Realizing natural communication between humans and machines is one of the objectives of artificial intelligence. Many businesses have developed various types of virtual voice assistants based on their usage of conversation systems technology in various apps and domains, such as Microsoft's Cortana, Amazon Alexa, Apple Siri, Computer Assistant, and Facebook's M. The new model will make use of many technologies, including image/video recognition, gesture recognition and speech recognition, to improve interaction between people and robots. In order to sense and affect the environment, a voice assistant incorporates artificial intelligence, speech recognition, machine learning, natural language processing (NLP), numerous actuation techniques, and speech synthesis. The proposed project is designed to associate virtual voice assistant to guide the user by detecting their initial emotions, such as Happy, Sad, Angry, Confused, etc. In our research, we focuses on  TTS (Text to Speech) module for the Virtual Voice Assistant and OpenCV for capturing the initial images for the detection of their emotions.},
        keywords = {Virtual Voice Assistant, OpenCV,  Emotion Detector.},
        month = {},
        }