Speech recognition based home automation
What you'll learn
- Learn basic concepts of speech recognition, the Jasper voice-control platform, and Snowboy hotword detction.
- Learn how to integrate Snowboy's offline hotword detection with Jasper's voice platform.
- Learn to connect appliances to the Raspberry Pi using relay modules.
- Program Jasper voice-controlled modules to control lights, fans, and a servo motor.
- Apply the above to setup a custom/personalized automation system.
- Basic knowledge of Linux - basic navigation, and ALSA configuration.
- Python programming knowledge - the regular expression operations module and file handling I/O
- Basic working knowledge of household appliances (fans, lights etc.) and circuitry.
This course will focus on teaching you how to set up your very own speech recognition-based home automation system to control basic home functions and appliances automatically and remotely using speech commands. Furthermore, we will teach you how to control a servo motor using speech control to move the motor through a required angle.
To learn how to automate your home, the best place to start is with your personal needs. So, in this course, we will focus on basic control of lighting and ventilation inside a home. This will give you a solid base to build upon by teaching you the basics required for simple speech-controlled automation and enable you to automate almost any appliance in your house – limited only by your creativity and knowledge.
Once we have grasped basic lighting control, we will move on to controlling a servo motor using PWM output from the Raspberry Pi GPIO pin. We will also use python file I/O to store the motor’s position.
This home automation course will involve teaching you how to control and automate lighting and ventilation appliances, with the potential for expansion of the system to control a variety of services and functions – from home appliances to monitoring and security systems. The system used for home automation will involve using Raspberry Pi 3 and writing python codes as modules for Jasper, which is an open-source platform for developing always-on speech controlled applications.
This course aims to help you attain control of household activities, and appliances via futuristic speech recognition. Using Speech-to-text and text-to-speech engines, it is possible to communicate effectively and efficiently with Jasper to carry out simple commands or tasks like activating, and deactivating relay switches to control home appliances without the need for physical exertion.
This course will also teach you how to modify the open source Jasper platform to use Snowboy hotword detection engine for offline speech recognition for keyword detection while using wit ai online speech recognition for command word detection. We do this as a precaution to safeguard the privacy of the user while retaining Jasper’s always listening feature.
Who this course is for:
- This course is meant for anyone with an interest in speech recognition and home automation.
- This course requires basic knowledge of the Raspberry Pi, Python programming, and Linux.
- This course is meant for intermediate-level programmers looking to create a personalized speech-control system.
Venkatesh Varadachari is the founder of MAKERDEMY, a pioneer maker education company head-quartered in Singapore.
Venkatesh believes that knowledge should be made available to people in all walks of life. Venkatesh also believes in the power of education to transform lives.
Venkatesh has an MBA from the prestigious Indian Institute of Management, Bangalore.
He also has a degree in Electrical Engineering from Madras University and a Masters in Financial Engineering from National University of Singapore.
Satyajeet is a passionate technology enthusiast and is excited about the possibility of impacting education through technology. Satyajeet holds a Masters in Computer Applications from VIT, one of the premier engineering institutes in India. He is a product engineer and spends his time creating exciting courses around the credit card sized Raspberry Pi.