CREATING DESKTOP SPEECH RECOGNISATION USING PYTHON PROGRAMMING

Abstract : As a personal assistant, this project is built with AI technologies, Artificial intelligence technologies are beginning to be actively used in human life, this is facilitated by the appearance and wide dissemination of the Internet of Things (IOT). Autonomous devices are becoming smarter in their way to interact with both a human and themselves. The advancement in technology over time has been unmeasurable. In such an era of advancement if people are still struggling to interact with their machine using various input devices then its not worth it. For this reason, many voice assistants were developed and are still being improved for better performance and efficiency. The main task of a voice assistant is to minimize the use of input devices like keyboard, mouse, touch pens, etc. This will reduce both the hardware cost and space taken by it.

 EXISTING SYSTEM :

 Desktop personal assistant is built with AI technologies, here Jarvis assists the end-user with day-to-day activities like general human conversation, searching queries in various search engines like Google, searching for videos in youtube, retrieving images, files in local drive, play songs in desktop by the use of imported modules like pyttsx3 is an offline module that is used for text to speech conversion in python, Date Time module is imported to support the functionality of date and time.web browser, Wikipedia, Google those are imported to fetch the user result. The user statements/commands are analysed with the help of Artificial intelligence to give an optimal solution.

 

 

 PROPOSED SYSTEM :

 The proposed system will have the following functionality: The system will keep listening for commands and the time for listening is variable which can be changed according to user requirements. If the system is not able to gather information from the user input it will keep asking again to repeat till the desired no. of times . The system can have both male and female voices according to user requirements. Features supported in the current version include playing music, emails, texts, search on Wikipedia, opening anything on the web browser, etc.

 

 

Deep Learning Covid-19 outbreak

MACHINE LEARNING UNDERSTANDING DEPTH

MACHINE LEARNING UNDERSTANDING DEPTH

MACHINE LEARNING 3-D DECONVOLUTIONAL NETWORKS

MACHINE LEARNING INTER-TURN SHORT-CIRCUIT

MACHINE LEARNING BASED ON JOURNALING

MACHINE LEARNING FUSING SELL-SIDE ANALYST

MACHINE LEARNING FAIRNESS IN SEMI-SUPERVISED LEARNING

MACHINE LEARNING ENRICHING THE TRANSFER LEARNING

MACHINE LEARNING AUTOMATED SCREENING SYSTEM

MACHINE LEARNING AN ONLINE TRANSFER LEARNING

MACHINE LEARNING THE HIDDEN SEXUAL MINORITIES

MACHINE LEARNING DEPTH ESTIMATION

MACHINE LEARNING A SYSTEMATIC LITERATURE

MACHINE LEARNING FREEDOM IN MANUAL TEXT

MACHINE LEARNING A SYSTEMATIC REVIEW

MACHINE LEARNING key based security

MACHINE LEARNING Deep Learning

MACHINE LEARNING EMOJI TEXT

MACHINE LEARNING EDGE COMPUTING MULTI-OBJECTIVE