||Speech Recognition using Machine Learning
||(Vineet Vashisht*) ; (Aditya Kumar Pandey) ; (Satya Prakash Yadav)
|| Speech recognition; Speech emotion recognition; Statistical classifiers; Dimensionality reduction techniques; Emotional speech databases; Vision processing; Computational intelligence; Machine learning; Computer visit
||Speech recognition is one of the fastest-growing engineering technologies. It has several applications in different areas, and provides many potential benefits. A lot of people are unable to communicate due to language barriers. We aim to reduce this barrier via our project, which was designed and developed to achieve systems in particular cases to provide significant help so people can share information by operating a computer using voice input. This project keeps that factor in mind, and an effort is made to ensure our project is able to recognize speech and convert input audio into text; it also enables a user to perform file operations like Save, Open, or Exit from voice-only input. We design a system that can recognize the human voice as well as audio clips, and translate between English and Hindi. The output is in text form, and we provide options to convert audio from one language to the other. Going forward, we expect to add functionality that provides dictionary meanings for Hindi and English words. Neural machine translation is the primary algorithm used in the industry to perform machine translation. Two recurrent neural networks used in tandem to construct an encoder?decoder structure are the architecture behind neural machine translation. This work on speech recognition starts with an introduction to the technology and the applications used in different sectors. Part of the report is based on software developments in speech recognition.