| Summary: | 碩士 === 朝陽科技大學 === 資訊與通訊系碩士班 === 98 === Study the implementation of voice recognition for a long time, many researchers to identify more complex sound. Use of voice recognition is usually associated with, or rules, to find out the meaning of the sound. Computer voice recognition techniques, the computer can use voice control. However, almost all of these voices voice or music, for the road will have to face sound of ambulance siren is very little recognition.
This paper presents an ambulance voice recognition method to Support Vector Machine as the basis of classification, the process is divided into the training process and the identification process. Training process, from the clean sound of an ambulance train whistle. Ambulance siren sound low frequency 600-750Hz, high-frequency 900-1050Hz for voice features, combined with Support Vector Machine as a voice recognition method. In the identification process, the use of recorded sound on the road. Cars ambulance siren sound mixing, and pure cars sound. 0.1 seconds the sound file to cut a frame, using the FFT to time domain data into frequency domain data. The frequency of interception we want to use the training received classify model, identify whether there is an ambulance siren sound.
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