ABSTRACT:
People with speech impairment find it difficult to communicate in a society where most of the people do not understand sign language. The idea proposed in this paper is a smart glove which can convert sign language to speech output. The glove is embedded with flex sensors and an. A novel method of State Estimation has been developed to track the motion of hand in three dimensional spaces. The prototype was tested for its feasibility in converting Indian Sign Language to voice output.Though the glove is intended for sign language to speech conversion. In order to overcome the complexity the artificial mouth is introduced for the dumb peoples. This system is based on the motion sensor. According to dumb people, for every motion they have a meaning. That message is kept in a database. Likewise all templates are kept in the database. In the real time the template database is fed into a microcontroller and the motion sensor is fixed in their hand. For every action the motion sensors get accelerated and give the signal to the microcontroller. The microcontroller matches the motion with the database and produces the speech signal. The output of the system is using the speaker. By properly updating the database the dumb will speak like a normal person using the artificial mouth.
PROPOSED SYSTEM:
The primary aim is to introduce an issue that will efficiently translate language gestures to every text and sensibility voice. The interpreter makes use of a glove based totally technique comprising of flex detector, instrument sensors. For each hand gesture created, a symptom is formed by the sensors appreciate the hand sign the controller matches the gesture with pre-stored inputs. The device not exclusively interprets alphabets but cans even sort words exploitation created gestures. A training mode is gettable on the device therefore it fits every user and accuracy is inflated. The device will even be able to translate larger gestures that require single hand movement. Gesture recognition implies a method by that knowledge is collected from parts of the physical body (usually the hand) and processed to work-out attributes like hand form, direction and speed of gesture being performed. There are presently 2 sorts of answer. Device based mostly techniques involve some variety of guide like a glove or glove-like framework fitted with position trackers and flex sensors to live the condition and position of the hand. Visual based mostly techniques use camera chase technologies, whereby usually the user wears a glove with specific colors or markers indicating individual parts of the hands, specially the fingers.
ADVANTAGES:
• Sensibility voice is easily understandable for user
• Reliable to operates and energy efficient
Block Diagram:
HARDWARE REQUIREMENTS:
• PIC microcontroller
• Two flex sensors
• Speech recognizing module
• Microphone
• Speaker
• LCD
• MEMS sensor
• Hand gesture
SOFTWARE REQUIREMENTS:
• MPLAB IDE software
• Embedded C language
CONCLUSION:
In this paper considering a Smart glove is used for recognizing the handmade gestures. A newly integrated proposed full duplex communication for voice impaired using this application is proposed. This artificial mouth helps the dumb people to interact normally like normal person. The motion sensor helps in gathering the data of the user. Each action will have its distinct significance. The accessibility of the gestures is enhanced than the previously proposed system. This makes the user feel like a normal person just with the help of smart glove.