4.1. Discussion
We have employed speech and vocal cord vibration to implement a type of mouth command control wheelchair. Below, we discuss some interesting problems.
4.1.1. Parameter setting in speech recognition
How can we improve the correct rate of speech recognition? A correct rate reaching 95% with 3 training sets is our demand, whatever the speech signals or vocal cord vibration signals. We discuss speech recognition parameters as follows:
1. Frame size:
A frame usually occupies 20~30 ms; we set 240 samples as a frame (sampling rate: 10000 sample/sec), occupying 24 ms; we tried 200 or 300 samples as a frame, and observed the correct rate.
2. Frame overlap:
Usually, a frame overlap occupies 1/2~2/3 frame size; we set the frame overlap at 160 samples (frame size: 240 points), occupying 2/3 frame size. We tried to set 1/2 or less 2/3 frame size as the frame overlap, and observed the correct rate.
4.1.2. Customized bio-signal acquiring module
In our present research, we have developed speech and vocal cords vibration recognition to control a wheelchair, although vocal cord vibration recognition is not as accurate as speech recognition. A bio-signal acquiring module should satisfy user needs and the situations they face. If possible, we will try to develop a new method, breathing vibration as a bio-signal acquiring method. We list bio-signal acquisition methods and tools.
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Table 4.1 Bio-signal control interfaces and tools
Bio-signal Tool Speech recognition Dynamic microphone
Condenser microphone Vocal cords vibration Dynamic microphone
Condenser microphone Accelerometer
Breathing vibration Piezoelectric materials Accelerometer
We have developed speech recognition and vocal cord vibration detection and transmission using a dynamic microphone as a possibly suitable tool for each bio-signal method.
4.1.3. Human system
A mature speech recognition system is one wherein the user’s input of any sentence could train the model. It is difficult to pronounce some specific speech or sentence for some users. If the system could achieve this standard, it would be helpful to users. If users command an instruction which does not belong to any speech model, the system should be able to simply ignore/reject it. Recently, certain systems have devoted efforts to achieving this objective.
As mentioned in Chapter 3, we employed three languages, separately, to test speech recognition. There were good recognition rates in Mandarin and Fukienese, but that for English was not as good.
4.2. Conclusion
At first, we see some real cases about paraplegia patients and then to have an idea of vocal cords controller. In order to achieve our idea, we meet many problems.
First, we develop a speech recognition system on PC-base, after which we embedded the program into NI cRIO. The controller FPGA module handled user input signal and output signal to wheelchair. The controller real-time processor operated via a speech recognition algorithm. When we accomplished that program embedded into
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cRIO, what remained to be done was mechanical and electrical integration.
We integrated the controller into the wheelchair and the battery in the wheelchair supplied power to the controller. The motors responded to the control signal.
With our background in computer science, in order to make the system perfect, we needed to cooperate with electrical integration engineers and physiotherapists who could explain the users’ actual needs.
If you want to know more about our system, you can to visit our website. We uploaded a demo video on our website. The hyperlink is as follows:
http:// sites.google.com/site/labview704/project
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Chapter 5: Future work
In the future, we hope the system which we have presented could be better perfected and more user friendly. More effort will be devoted to the following:
1. Customized control interface to satisfy users:
Wheelchair integration could be friendlier. There is only a single speed to steer wheelchair. We can add a speed control to controller to render it more secure and allowing the user to steer the wheelchair as desired.
We should engage in more discussions with doctors regarding patients’ needs, as they possess expert opinion. Our goal is to develop a system that in generally acceptable for hand disabled users, suitable for mass production and at low cost.
2. To develop a controller suitable for MD patients:
MD is described in [13], as an inherited disorder that causes progressive muscle weakness (myopathy) and atrophy (loss of muscle mass) due to defects in one or more genes required for normal muscle function; the primary symptom for most types of MD is muscle weakness; patients even have difficulties in speaking out a word, or are only able to vibrate their abdomen in some serious cases. We tend to specialize our system in order to help them by developing a system which can be expanded in order to permit more features of command, such as abdomen vibration.
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