Voice behavior assessment and evaluation method for rail transit transportation simulation training
A simulation training and rail transit technology, applied in speech analysis, speech recognition, teaching aids for electrical operation, etc., can solve the problems of students not being able to know, students' voice evaluation, etc., to eliminate manual evaluation, intuitive standardization and accuracy, The effect of improving system performance
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Embodiment 1
[0060] A voice behavior evaluation method for rail transit simulation training, such as figure 1 shown, including the following steps:
[0061] S101: Use intelligent speech recognition technology to recognize the voice communication information of the trainees during the training process and convert it into text information;
[0062] S102: Judging and extracting all keywords in the entire sentence through keyword recognition technology, and classifying the extracted keywords according to semantic correlation, device correlation, and technical term correlation;
[0063] S103: Obtain standard voice data after automatically recognizing the voice communication information through the deep neural network, and match the standard voice data with the voice evaluation database to obtain unique matching standard evaluation data;
[0064] S104: After comparing and analyzing the standard voice data and the standard evaluation data, it is judged whether the semantics of the voice communic...
Embodiment 2
[0098]The voice communication information is described as "the locomotive moves slightly, the allowable speed is 5 km / h, and walks to the front of the exit signal machine" as the input signal. Assume that the voice of the voice evaluation database is "the permitted speed of the locomotive is 5 km / h, and go to the exit signal machine". When the system recognizes the voice signal, it first converts the voice information into text information through the intelligent voice recognition program developed by the TTS engine in the Windows Speech SDK development kit.
[0099] Among them, the keyword recognition technology mainly compares the input signal with the keyword database one by one, and can respectively obtain the semantic-related keywords, equipment-related keywords, and technical term-related keywords contained in the input signal. The standard keyword database recognition system detects whether this input signal contains keywords. This method has a fast response speed.
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