Method for quickly recognizing speech emotion category based on long and short term memory network
A long-short-term memory and speech recognition technology, which is applied in speech analysis, instruments, etc., can solve the problems of increasing computational complexity and achieve the effects of reducing computational complexity, good application prospects, and reducing the amount of matrix calculations
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[0048] The present invention will be further described below in conjunction with the accompanying drawings.
[0049] The invention discloses a method for quickly identifying speech emotion categories based on a long-short-term memory network, which includes the following steps:
[0050] Step A, extract frame-level speech features with timing information from the original speech data, wherein, the speech features retain the timing information in the original speech data through the sequence relationship between speech frames, and the dimension of the speech features varies with the original Varies with the actual length of the voice data. The detailed speech feature set is shown in Table 1 below:
[0051] Table 1
[0052] voice features describe voiceProb Ratio of voiced sound HNR glottal harmonic-to-noise ratio F0 Baseband F0raw Original base frequency without unvoiced threshold F0env F0 envelope jitterLocal Periodic first...
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