Speech is the most important way of communication for people. Using the speech as the interface for processes became more important with the improvements of artificial intelligence. In this project, it is implemented to control a wheelchair with speech comment. Speech commends were taken to the computer by the microphone, the features were extracted with The Mel Frequency Spectral Coefficients algorithms and they were recognized by the help of Artificial Neural Networks. Finally, the comments have converted the form in which the wheel chair can recognize and move accordingly. Our proposed system aim at a robotic vehicle operated by human speech commands. The system operates with the use of an android device which transmits voice commands to raspberry pi to achieve this functionality. The transmitter consists of the android phone Bluetooth device. The voice commands recognized by the module are transmitted through the Bluetooth transmitter. These commands are detected by the wheel chair in order to move it in left, right, backward and front directions. The Bluetooth receiver mounted on raspberry pi is used to recognize the transmitted commands and decode them. The controller then drives the vehicle motors to move it accordingly. This is done with the use of a driver IC used to control the motor movements. The Bluetooth technology used to transmit and receive data allows for remotely operating the system within a good range. Voice operated robot is used for one moving object is developed such that it is moved as per commands are given by the voice recognition module and that command is received by robot and robot is matched the given command with stored program and then set the command as per voice using wireless communication.

1. Voice controlled robotic wheel chair Using raspberry pi 3 and Arduino uno
Name of Students Under the guidance of
Monu Singh (1500121015) Mr. Puneet kumar chaudhary
Narendra Kumar(1400121024) Assist. Professor
Tushar Gupta(1500121024)
ELECTRICAL & ELECTRONICS DEPARTMENT
ANAND ENGINEERING COLLEGE, KEETHAM AGRA-282007
Introduction :-
Speech is the most important way of communication for people. Using the speech as the
interface for processes became more important with the improvements of artificial intelligence.
In this project, it is implemented to control a wheel chair with speech comment. Speech
commends were taken to the computer by the microphone, the features were extracted with The
Mel Frequency Spectral Coefficients algorithms and they were recognized by the help of
Artificial Neural Networks. Finally, the comments have converted the form in which the wheel
chair can recognize and move accordingly. Our proposed system aim at a robotic vehicle
operated by human speech commands. The system operates with the use of an android device
which transmits voice commands to raspberry pi to achieve this functionality. The transmitter
consists of the android phone Bluetooth device. The voice commands recognized by the module
are transmitted through the Bluetooth transmitter. These commands are detected by the wheel
chair in order to move it in left, right, backward and front directions. The Bluetooth receiver
mounted on raspberry pi is used to recognize the transmitted commands and decode them. The
controller then drives the vehicle motors to move it accordingly. This is done with the use of a
driver IC used to control the motor movements. The Bluetooth technology used to transmit and
receive data allows for remotely operating the system within a good range. Voice operated robot
is used for one moving object is developed such that it is moved as per commands are given by
the voice recognition module and that command is received by robot and robot is matched the
given command with stored program and then set the command as per voice using wireless
communication.
A system of wheelchair is designed which is operated using voice Commands and is useful for
the person who is physically challenged. This model explains the speech recognition to provide
the hi tech approach towards the goal that is to operate wheelchair with less efforts. By using
speech recognition technique for controlling the wheelchair, we have to speak into the
microphone and the Raspberry pi B follows the commands and perform the operations on the Dc
motor. This model presents the concept of speech recognition . In this way, a navigation
framework for wheelchairs in which integrates various alternative input interfaces where voice
control is done with voice recognition module. This enables patient with limited control over
their limbs to navigate using voice commands.

2. Speech is the most used way of communication for people. We born with the skills of speaking,
learn it easily during our early childhood and mostly communicate with each Other with speech
throughout our lives. By the developments of communication technologies in the last era, the
speech starts to be an important interface for many systems. Instead of using complex different
interfaces, speech is easier to communicate with computers. In this project, it is aimed to control
a robot with speech commands. The robot is able to Recognize spoken commands to move
correctly. To give a direction to the robot, first, the voice command is sent to the computer using
a microphone. The computer recognizes the command by speech recognition system. And then
computer converts the voice command to direct command that predefined and recognizable by
the robot. When the robot gets the direction command, it moves according to the spoken
command.
This project Voice Controlled Robotic Vehicle helps to control robot through voice commands
received via android application. The integration of control unit with Bluetooth device is done to
capture and read the voice commands. The controlling device may be any android based
Smartphone/tab etc having an android OS. The android controlling system provides a good
interactive GUI that makes it easy for the user to control the vehicle. The transmitter uses an
android application required for transmitting the data. The receiver end reads these commands
and interprets them into controlling the robotic vehicle. The android device sends commands to
move the vehicle in forward, backward, right and left directions. After receiving the commands,
the microcontroller then operates the motors I order to move the vehicle in four directions. The
communication between android device and receiver is sent as serial communication data
Definition of Speech Recognition :- Speech recognition is the process of converting the speech
signal to a sequence of word by means of an algorithm implemented as a program which is also
known as Automatic speech recognition (ASR). Basically speaker independent systems are most
widely used because voice training is not used there. Speech recognition is classified as
connected word recognition and isolated word recognition. So the speech recognition is nothing
but the pattern matching based on training and recognition. Speech signal is characterized. For
this system the input taken as human voice signal.
This voice signal is detected by the USB microphone which is connected to the raspberry pi B.
After passing some of the sequence of steps, words are recognized. The output of the recognized
word is displayed on the terminal window. Using the gpio pins of the Raspberry pi these signals
are transmitted to the dc motor and according to that the action is performed.
Keyword : raspberry pi3, Arduino programming, python language

3. Literature survey :-
1. Chin-Tuan Tan and Brian C. J. Moore, “Perception of nonlinear distortion by
hearing-impaired people,”
Abstract: In this paper Objective quality measures have a long history in the
speech and audio community, with a wide variety of measures reported in the
literature. Some of the earliest objective quality measures quantified the
difference between a degraded signal and its corresponding clean version using
relatively simple calculations based on signal-to-noise ratio
2. Oberle, S., and Kaelin, A. "Recognition of acoustical alarm signals for the
profoundly deaf using hidden Markov models,"
Abstract: A new acoustical alarm signal recognition scheme for tactile hearing aids
using hidden Markov models (HMM's) is presented. In particular, a maximum
likelihood classifier is proposed where the observation probability density function of
each alarm class is modeled by a four-state HMM
3. Q. Y. Hong, C. H. Zhang, X. Y. Chen, and Y. Chen, “Embedded speech
recognition system for intelligent robot,”
Abstract: “Infrared navigation—Part I: An assessment of feasibility,” IEEE
Trans. Electron Devices, vol. ED-11, pp. 34-39, Jan. 1959. Speech synthesis is
done by using raspberry pi only and is achieved by using pocket Sphinx. Speech
synthesis is used for the vocal response from the raspberry pi
C. M. Higgins and V. Pant, “Biomimetic VLSI sensor for visual tracking of
small moving targets”
Abstract : Taking inspiration from the visual system of the fly, we describe and
characterize a monolithic analog very large-scale integration sensor, which
produces control signals appropriate for the guidance of an autonomous robot to
visually track a small moving target
F. Daerden and D. Lefeber,” The concept and design of pleated pneumatic
artificial muscles”
Abstract : This paper describes the design of a new type of Pneumatic Artificial
Muscle (PAM), namely the Pleated Pneumatic Artificial Muscle (PPAM). It was
developed as an improvement with regard to existing types of PAM, e.g. the
McKibben muscle.

4. Methodology:-
The block diagram which includes all the components of the wheelchair. USB microphone is
used to send the voice commands to the raspberry pi and after that voice recognition module is
used for the speech recognition which display the voice commands
Raspbery pi
Software Requirement :-
1. Arduino IDE.
2. Google speech API.
3. Coding language : (1) Arduino programming (java & C++).(2) Raspberry pi
programming (python)
Arduino
Transmits orders
from raspbery pi to
motor
Listener Thread
Listen to message
coming from the
Arduino
Command Thread
Send message to the Arduino
Main Thread
- PD controller
- starts all the
Thread
Voice processing
Thread
Detect the voice and execute
the voice
Voice Analyser
Thread
Retrieves the current
voice from the USB mic
and put it in a
queue
USB microphone
Motors

5. Proposed work :-
Based on above Exhautive Literature Review of Various Topologies, voice controlled robotic
wheel chair using raspberry pi work is proposed for the project:
1. To investigate different method of voice control board module
2. Investigation on Different voice control techniques
3. To design the model using proteous
4. To investigate the method to interface between hardware & software
5. To investigation on methodology for voice recognition
6. Several studies have concluded that the independent mobility or movement which is
included powered wheel chair, manual wheelchair and walker access the benefit to all
the disabled human beings .
Reference :-
[1].Chin-Tuan Tan and Brian C. J. Moore, “Perception of nonlinear distortion by hearing-
impaired people,” International Journal of Ideology 2008,Vol. 47, No. 5 , Pages 246-256.
[2].Oberle, S., and Kaelin, A. "Recognition of acoustical alarm signals for the profoundly
deaf using hidden Markov models," in IEEE International symposium on Circuits and
Systems (Hong Kong), pp. 2285-2288., 1995.
[3].A. Shawki and Z. J.,“A smart reconfigurable visual system for the blind”, Proceedings of
the Tunisian-German Conference on: Smart Systems and Devices, 2001.
[4].C. M. Higgins and V. Pant, “Biomimetic VLSI sensor for visual tracking of small moving
targets”, IEEE Transactions on Circuits anSystems, vol. 51, pp. 2384– 2394, 2004.
[5].F. Daerden and D. Lefeber,” The concept and design of pleated pneumatic artificial
muscles”, International Journal of Fluid Power, vol. 2, no. 3, 2001, pp. 41–45