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Voice Recognition System Circuit Diagram [EXCLUSIVE]

This article details the construction and building of a stand alone trainable speech recognition circuit that may be interfaced to control just about anything electrical, such as; appliances, robots, test instruments, VCR's TV's, etc. The circuit is trained (programmed) to recognized words you want it to recognize.

Voice Recognition System Circuit Diagram

The heart of the circuit is the HM2007 speech recognition integrated circuit. The chip provides the options of recognizing either forty .96 second words or twenty 1.92 second words. This circuit allows the user to choose either the .96 second word length (40 word vocabulary) or the 1.92 second word length (20 word vocabulary). For memory the circuit uses an 8K X 8 static RAM.

The SR-07 circuit we are building operates in the manual mode. The manual mode allows one to build a stand alone speech recognition board that doesn't require a host computer and may be integrated into other devices to utilize speech control.

Currently most speech recognition systems available today are programs that use personal computers. The add on programs operate continuously in the background of the computers operating system (windows, OS/2, etc.). These programs require the computer to be equipped with a compatible sound card. The disadvantage in this approach is the necessity of a computer. While these speech programs are impressive, it is not economically viable for manufacturers to add full blown computer systems to control a washing machine or VCR. At best the programs add to the processing required of the computer's CPU. There is a noticeable slow down in the operation and function of the computer when voice recognition is enabled.

We take our ability to listen for granted. For instance we are capable of listening to one person speak among several at a party. We sub-consciously filter out the extemporaneous conversations and sound. This filtering ability is beyond the capabilities of today's speech recognition systems.

Speech recognition is not speech understanding. Understanding the meaning of words is a higher intellectual function. Because a computer can respond to a vocal command does not mean it understands the command spoken. Voice recognition system will one day have the ability to distinguish linguistic nuances and meaning of words, to "Do what I mean, not what I say!"

The post details 3 simple sound activated relay switch circuits which can used as a module for any system that might be assigned to trigger by detecting some kind of sound pressure level.Or simply applications such as a voice activated alarm security circuit.

Utilizing this basic sound activated switch design, toggling a system by a sound pulse could be done very effectively, not only with a robotic system but as well as for any desired of home automation. As an illustration the circuit could be used like a sound-activated light bulb to illuminate a porch light in response to a knock on the front door.

Voice controlled wireless smart home system has been presented for elderly and disabled people. The concept ofcontrolling home appliances using human voice is interesting. The proposed system has two main components, they are

(a) voice recognition system, and (b) wireless system. This system to control home appliances uses a voice controlled android application. By the increasing use of PC (personal computers), internet, mobile phone and wireless technology, it makes it easy for a user to remotely access and control the appliances.

The main aim of our system is to build a perfect companion for someone to be at home. Generally, home automation research targeted many needs like applications that provide the luxury and smart requirements while some threw light on the special needs for elderly and disabled etc. our system is a computer based system that can accept voice to direct commands and process them. The system provides us switching any device ON/OFF.

Android is a mobile operating system based on Linux kernel and currently developed by Google. We prefer android platform because of its huge market globally and it is easy to use user interface. The voice recognizer which is an inbuilt feature of android phones is used to build an application which the user can operate to automate the appliances at his house. For wireless communication system a Bluetooth module HC-05 is used as a remote which is connected to the control unit for sensing the signals sent by the android voice application.

The application first searches for the Bluetooth device. If it is available then it launches the voice recognizer. It reads the voice and converts the audio signal into string. It provides a value for each appliance which will be fed to the microcontroller device. The microcontroller uses the port in serial mode. After reading the data it decodes the input value and sends a signal to the parallel port through which the relay circuit will be activated.

Sir in this step 2,in the circuit diagram the relay board is takes output from analog inputs of adruino,,,it's is really works and plz tell the programe witten is for 4 chennal relay module or 2 channel relay module

In this paper, a neuromorphic crossbar circuit with binary memristors is proposed for speech recognition. The binary memristors which are based on filamentary-switching mechanism can be found more popularly and are easy to be fabricated than analog memristors that are rare in materials and need a more complicated fabrication process. Thus, we develop a neuromorphic crossbar circuit using filamentary-switching binary memristors not using interface-switching analog memristors. The proposed binary memristor crossbar can recognize five vowels with 4-bit 64 input channels. The proposed crossbar is tested by 2,500 speech samples and verified to be able to recognize 89.2% of the tested samples. From the statistical simulation, the recognition rate of the binary memristor crossbar is estimated to be degraded very little from 89.2% to 80%, though the percentage variation in memristance is increased very much from 0% to 15%. In contrast, the analog memristor crossbar loses its recognition rate significantly from 96% to 9% for the same percentage variation in memristance.

In realizing memristor-based synaptic systems, a crossbar circuit that is made of only passive memristors can be thought of as the densest and simplest architecture among various synaptic circuits that have been developed previously. If a crossbar circuit is made of both memristors and selectors such as transistors and diodes, this kind of hybrid-type crossbar circuit is difficult to be stacked layer by layer. Thus, the pure crossbar circuit with only passive memristors can be a key element to implement the densest and simplest three-dimensional architecture of neuromorphic systems.

In this paper, we propose a binary memristor crossbar circuit for recognizing five different vowels. The block diagram and the detailed circuit schematic are shown and explained in the following section. In addition, the circuit simulation and statistical simulation are performed, and the simulation results are discussed and finally summarized in this paper [18].

In this paper, the binary memristor crossbar circuit was proposed for neuromorphic application of speech recognition. Compared with analog memristors that are rare in available materials and need a complicated fabrication process, binary memristors which are based on the filamentary-switching mechanism are found more popularly and easy to be fabricated. Thus, we developed the neuromorphic crossbar circuit using filamentary-switching binary memristors instead of interface-switching analog memristors. The proposed binary memristor crossbar could recognize five vowels with 64 input channels and a 4-bit resolution. The proposed crossbar array was tested by 2,500 speech samples and verified to be able to recognize 89.2% of the total tested samples. Moreover, the recognition rate of the binary memristor crossbar is degraded very little only from 89.2% to 80%, even though the percentage statistical variation in memristance is increased from 0% to 15%. In contrast, the analog memristor crossbar is degraded significantly from 96% to 9% with the same percentage variation in memristance.

This module has a 5V TTL serial port and 16 I/O ports, which can communicate with external single-chip microcomputer, exchange information, and can also control relay and other equipment. Therefore, the voice recognition module is directly connected with the relay to control the lifting of the push rod motor.

The project aims at controlling a wheelchair by means of human voice. It enables a disabled person to move around independently, using a voice recognition application which is interfaced with motors. The prototype of the wheelchair is built using a micro-controller, chosen for its low cost, in addition to its versatility and performance in mathematical operations and communication with other electronic devices. The system has been designed and implemented in a cost effective way so that if our project is commercialized the needy users in developing countries will benefit from it.

The speech recognition system is acompletely assembled and easy to useprogrammable speech recognition circuit.Programmable, in the sense that you train the words (or vocal utterances) you want the circuit to recognize. This board allows you to experiment with many facets of speech recognition technology. It has 8 bitdata out which can be interfaced with anymicrocontroller for further development. Some of interfacing applications which can bemade are controlling home appliances, robotics movements, Speech Assisted technologies, Speech to text translation, and many more

A. Whole circuit diagram of our project is shown above fig. 9v battery is connect across 100µ 7805 IC is used, this IC is used to give constant dc 5v.output of this Ic is connect to pin no 40 of microcontroller AT89C52.output of voice module is connected with port1 of the At89c52. Then output of port2 is given to input of motor driver circuit. which drive the motor in clockwise and counterclockwise.12v and 40A battery is connected with motor driver circuit. 041b061a72


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