Learning device, voice interval detector, and method for detecting voice activity
A sound interval and learning device technology, which is applied in neural learning methods, speech analysis, biological neural network models, etc., can solve the problems of low detection accuracy of sound intervals and the inability to properly distinguish noise and sound, and achieve the effect of improving detection accuracy
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[0031] figure 1 It is a block diagram showing the configuration of the speech interval detection system 1 including the learning device 2 and the speech interval detection device 3 according to Embodiment 1 of the present invention. The learning device 2 generates a synthetic neural network (hereinafter referred to as synthetic NN) b by inputting learning data a, and learns a Gaussian mixture model of noise and sound (hereinafter referred to as noise and sound GMM) c. The voice interval detection device 3 detects the voice interval of the input signal based on the synthesized NN b, the noise and the voice GMM c, and the noise Gaussian mixture model (hereinafter referred to as noise GMM) d, and outputs the voice interval detection result.
[0032] Learning data a is data including spectral feature quantities of noise data and voice data. The spectral feature quantity is, for example, 1-dimensional to 12-dimensional vector data of Mel-frequency cepstral coefficients (hereinafte...
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