Automatic speech recognition method and system based on artificial intelligence
A technology of automatic speech recognition and artificial intelligence, applied in speech recognition, speech analysis, instruments, etc., can solve problems such as low efficiency of professional vocabulary recognition and inaccurate recognition of professional vocabulary, so as to reduce professional misunderstandings, improve professionalism, and improve search speed effect
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[0080] Example 1:
[0081] The embodiment of the present invention provides an automatic voice recognition method based on artificial intelligence. figure 1 For a flow chart of an automatic speech recognition method based on artificial intelligence, please refer to figure 1 The method includes the following steps:
[0082] Step S101 receives the voice signal to be identified;
[0083] Step S102, the speech signal to be identified is pre-processed to obtain a voice input signal;
[0084] Step S103, perform the conversion of the speech input signal to the frequency domain, extract speech feature parameters;
[0085] Step S104, random samples of the speech feature parameters, obtain several sample feature parameters;
[0086] Step S105, input the sample feature parameters to the acoustic model and the language model, and the decoded search acquisition recognition result is obtained;
[0087] In step S106, the identification result is input to the vocabulary classification template, a...
Example Embodiment
[0097] Example 2:
[0098] Based on the first embodiment, after the corresponding text, the corresponding text is included, including:
[0099] Enter the text of the output to the spelling error correction model, obtain the text after error correction;
[0100] Output of the error after the end text is output.
[0101] The working principle and beneficial effect of the above technical solution is that the scheme used in this embodiment is the process of spelling the error correction of the input text. After the acoustic model and the language model, the text thereof may exist in the form of a spelling error. Question, in order to ensure the accuracy and professionalism of automatic voice recognition, the spelling of the output text is required to correct the output of the output. By setting the spelling error correction model to ensure that the final text of the output does not have the form of spelling errors, improve the accuracy of automatic voice recognition. .
Example Embodiment
[0102] Example 3:
[0103] Based on the first embodiment, the word constituent template construction method includes:
[0104] Get a large number of professional vocabulary that belong to different industries;
[0105] The professional vocabulary uses convolutional neural networks to classify training in accordance with the industry to which the professional vocabulary belongs;
[0106] Get the classification result and store the classification result in a classified database, and constitute the vocabulary classification template.
[0107]The operation principle of the above technical solution is that the scheme used in this embodiment is a description of the construction method of the vocabulary classification template. By getting a large number of professional vocabulary, the convolutional neural network is used to classify the above-mentioned professional vocabulary according to the industry-based, which is different from the professional vocabulary contained in different indus...
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