Gesture Vocalizer

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  • Topic: Gesture, Speech synthesis, Microelectromechanical systems
  • Pages : 9 (2755 words )
  • Download(s) : 336
  • Published : March 15, 2013
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Microcontroller and Sensors Based Gesture Vocalizer

Abstract: - Gesture Vocalizer is a large scale multi-microcontroller based system being designed to facilitate the Communication among the dumb, deaf and blind communities and their communication with the normal people. This system can be dynamically reconfigured to work as a “smart device”. In this paper, microcontroller and sensors based gesture vocalizer is presented. Gesture vocalizer discussed is basically a data glove and a microcontroller based system. Data glove can detect almost all the movements of a hand and microcontroller based system converts some specified movements into human recognizable voice. The data glove is equipped with two types of sensors: The bend sensors and accelerometers as tilt sensors. This system is beneficial for dumb people and their hands will speak having worn the gesture vocalizer data glove.

1 Introduction

“Speech” and “gestures” are the expressions, which are mostly used in communication between human beings. Learning of their use begins with the first years of life. Research is in progress that aims to integrate gesture as an expression in Human- Computer Interaction (HCI). In human communication, the use of speech and gestures is completely coordinated. Machine gesture and sign language recognition is about recognition of gestures and sign language using computers. A number of hardware techniques are used for gathering information about body positioning; typically either image-based (using cameras, moving lights etc) or device-based (using instrumented gloves, position trackers etc.). However, getting the data is only the first step.The second step, that of recognizing the sign or gesture once it has been captured is much more challenging, especially in a continuous stream. Infact currently, this is the focus of the research. This research paper analyses the data from an instrumented data glove for use in recognition of some signs and gestures. A system is developed for recognizing these signs and their conversion into speech. The results will show that despite the noise and accuracy constraints of the equipment, the reasonable accuracy rates have been achieved.

2. Methodologies

[pic]

Block diagram of the system is shown Fig.1. The system is consisted of following modules: • Data Glove
• Tilt detection
• Gesture detection
• Speech Synthesis
• LCD Display
Data glove is consisted of two sensors; bend sensors and tilt sensor. The output of the tilt sensors is detected by the tilt detection module, while the output of the bend sensors and the overall gesture of the hand are detected by the gesture detection module. The gesture detection module gives an 8-bit address to speech synthesis module; 8-bit address is different for each gesture. Speech Synthesis module speaks the message respective to address received by it.

3. System Descriptions

3.1 Data Glove

Data glove is consisted of two sensors; bend
Sensors and tilt sensor

3.1.1Bend sensor

In this research setup data glove is equipped with five bend sensors, each of the bend sensor is meant to be fixed on each of the finger of the hand glove for the monitoring and sensing of static movements of the fingers of the hand. The bend sensor is made by using 555 timer IC in astable mode along with a photo transistor. The output of the bend sensor is a square wave. Frequency of this output wave varies with the [pic]bending of the bend sensor. Circuit diagram of bend sensor is shown below in Fig.2. Each bend sensor has its own square output which is required to be transferred to the third module of the system where pulse width of the output of each bend sensor is calculated with the help of microcontroller.

3.1.2 Tilt Sensor

Accelerometer in the Gesture Vocalizer system is used as a tilt sensor, which checks the tilting of the hand. ADXL103 accelerometer is used in the system, the accelerometer has an analog output, and this...
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