Presentation Information
[23p-A302-10]Speech Recognition with Time-Delayed In-Materio Reservoir Computation
〇(M2)Ahmet KARACALI1, Oradee Srikimkaew1, Yuki Usami1,2, Hirofumi Tanaka1,2 (1.LSSE, Kyushu Inst. Technol. (Kyutech), 2.Neuromorphic Center, Kyutech)
Keywords:
Reservoir Computing,Speech Recognition,MFCC
The physical RC device performs more efficiently in reservoir computation than conventional neuron network systems in terms of power consumption. In this study, we used this physical reservoir device for speech classification. Firstly, the audio files in the free-speech cascaded dataset were converted into electrical signals. Then, time series data were collected with the time-delayed reservoir device by applying the MFCC (Mel-Frequency Cepstral Coefficients) feature selection algorithm. This time series data was trained and speech classification was performed.