Voice Control Device using Natural Language Processing and Raspberry Pi

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Description

Voice Control Device using Natural Language Processing and Raspberry Pi

Objective:

In this paper, we aim to design a home controlling system using NLP


Voice Control Device using Natural Language Processing and Raspberry Pi

Abstract 

Home automation – controlling the fans, lights, and other electrical appliances in a house using the Internet of things is widely preferred in recent days. In this paper, we propose a web application using which the fans, lights, and other electrical appliances can be controlled over the Internet. The important feature of the web application is that firstly, we have a chatbot algorithm such that the user can text information to control the functioning of the electrical appliances at home. The messages sent using the chatbot are processed using Natural Language processing techniques. Secondly, any device connected to the local area network of the house can control the devices and other appliances in the house. Thirdly, the web application used to enable home automation also has a security feature that only enables certain users to access the application. And finally, it also has the functionality of sending an email alert when an intruder is detected using motion sensors.


Voice Control Device using Natural Language Processing and Raspberry Pi

Existing systems:

  • Remote-controlled device automation
  • Web-based device control
  • Sensor-based automation 
  • Manual controlled 

Voice Control Device using Natural Language Processing and Raspberry Pi

Proposed system:

This system is designed for controlling the home or any indoor environment devices. It is designed and implemented around the raspberry pi embedded computer. Her voice command is used for controlling the devices. For this purpose, a simple interactive chatbot is created using natural language processing. Python language is used for creating the chatbot, in the python NLTK module can be used for creating a simple chatbot. This system can be used for controlling any indoor devices. Here Bluetooth communication can be used for giving voice input, since raspberry pi has an inbuilt Bluetooth module no need to use an external Bluetooth module. Command sending end is a smartphone with a Bluetooth application with a voice recognition capability.


Block diagram:                       

Voice Control Device using Natural Language Processing and Raspberry Pi
Voice Control Device using Natural Language Processing and Raspberry Pi

Block diagram description:

  • Here raspberry pi acts as the main unit of the whole system
  • Every other hardware device is connected to it 
  • Here inbuilt Bluetooth in raspberry pi is used for connecting the android application with the system
  • Android application is used for giving voice input 
  • This input is converted to text and this text can be used as input for to chatbot 

Hardware tools:

  • Raspberry pi
  • Electrical Loads
  • Smartphone

Software tools: 

  • Python IDLE
  • Raspbian OS 
  • Bluetooth application 

REFERENCES

[1] M. R. and D. Subramaniyan, “Personal Assistant and Intelligent Home Assistant via Artificial Intelligence Algorithms- (Raspberry PI/Pineapple)”, Impact: International Journal of

Research in Engineering & Technology (IMPACT: IJRET), vol.4, no. 6, pp. 9-13, 2016.

[2] Ass. Prof. Emad S. Othman, “Voice Controlled Personal Assistant using Raspberry PI,” International Journal of Scientific & Engineering Research, vol. 8, no. 11, pp. 1611–1615, Nov. 2017.

[3] Dahl, George E., et al. “Context-dependent pre-trained deep neural networks for large-vocabulary speech recognition.” Audio, Speech, and Language Processing, IEEE Transactions

on 20.1 (2012): 30-42.

[4] Chelsea, Ciprian, et al. “Large scale language modeling in automatic speech recognition.” arXiv preprint arXiv:1210.8440 (2012).

[5] Schultz, Tanja, Ngoc Thang Vu, and Tim Schlippe. “GlobalPhone: A multilingual text & speech database in 20 languages.” Acoustics, Speech, and Signal Processing

(ICASSP), 2013 IEEE International Conference on. IEEE, 2013.

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