25-08-2017, 09:32 PM
DSP Based Speech Operated Home Appliances Using Zero Crossing Features
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Abstract
The main idea of this paper is to build a simple speech recognition system using Digital Signal
Processor (DSP) that controls home appliances (i.e. turning on/off) by processing the spoken
word. The method used is simple, involving a plain count of the frequency of zero crossings. Two
features of zero-crossing are used namely: maxima & running sum that increases the accuracy of
recognition. The DSP calculates the zero crossings of the spoken words and accordingly
generates different analog signals at its output. These analog signals are further processed so as
to operate the appliances. The words chosen for recognition are ‘ONE’, ‘TWO’ and ‘THREE’.
The paper includes two approaches for implementation of speech recognition into DSP, using
Matlab Simulink approach and secondly using Code Composer Studio (CCS). Moreover the first
approach performs offline processing and the other performs real time processing of words. The
results at the end describe the efficiency of the system.
INTRODUCTION
Speech recognition is a vast topic of interest and is looked upon as a complex problem. In a
practical sense, speech recognition solves problems, improves productivity, and changes the way
we run our lives. Reliable speech recognition is a hard problem, requiring a combination of many
techniques; however modern methods have been able to achieve an impressive degree of
accuracy [1]. Real-time digital signal processing made considerable advances after the
introduction of specialized DSP processors. Suitable DSP Starter Kits, with specific DSP
processor and related software tools such as assemblers, simulators and debuggers are
available to make system design and application development easier. Digital Signal Processor
TMS320C6713 enables to design a system with very high computational power and large
memory space with minimal count of components what safes printed circuit board space and
simplifies design [2,3].
Talking to appliances in a home has been a science fiction staple for decades. This paper
proposes solution for providing speech interface to electronic devices in a home. The
TMS320C6713 digital signal processor (DSP) and Microcontroller are used in this work. The DSP
is used for implementing speaker dependent speech recognition system for capturing vocal
commands for operating the appliances and the Microcontroller serves as the main interface
between DSP and the control circuit handling the appliances.
THE PROPOSED SYSTEM MODEL
The system model of Figure 1 consists of two parts. First part informs about interfacing and
processing of the spoken word using floating point DSP Starter kit (DSK) TMS320C6713. DSK is
used for the research module because it provides an efficient and stable DSP development The second part consists of control circuitry that consists of hardware that operates the
appropriate appliance through the command recognized by DSK.
The system model consists of:
The TMS320C6713 Processor for Speech Recognition
The system model uses Texas Instrument TMS320C6713 DSP Processor to perform the task of
speech recognition. The Processor first filters the noise from input speech. It then processes and
identifies the spoken word. For the identified word, the Processor generates an analog sinusoidal
signal of certain frequency. For example, for the audio command ‘ONE’, the Processor generates
a sinusoidal signal of frequency 400Hz. Thus sine waves of different frequencies are generated at
output of Processor for each spoken word ‘ONE’, ‘TWO’ and ‘THREE’ as shown in the Table 1.
The Hardware Control Circuitry
The control circuitry consists of Frequency to Voltage (F to V) converter, Analog to Digital (A to D)
converter, AT89C52 Microcontroller, relay drivers and relays.
The analog signals at the output of Processor are passed to F to V converter. The audio
commands ‘ONE’,’ TWO’ and ‘THREE’ are mapped into three different voltage levels by F to V.
These voltage levels are then digitalized by ADC0804. AT89C52 Microcontroller operates the
appropriate relays scanning its digital input. These relays then in turn operate the corresponding
appliances like; lamps, fan, dishwashers, clothes washers, dryers, microwaves, refrigerators,
freezers, etc., switching them either ON or OFF. For example if the spoken word is ‘ONE’, then
home appliance one will toggle ( i.e. if it is ON then it will turn OFF and vice versa), if say the
spoken word is ‘TWO’ then home appliance two will toggle.
CONCLUSION
The paper presents two approaches for implementing speech recognition algorithm; using Matlab
Simulink approach and secondly using Code Composer Studio (CCS) using DSK TMS320C6713.
The algorithms are based on zero crossing feature. The simulations as well as experimental
results of the hardware circuit are included. These results indicate that the home appliances can
be operated reliably with voice commands. The proposed method also finds promising
applications in robot control and helpful for industries where there is immense danger in operating
the system manually.