Text regularization model training method and device, text regularization method and device

Abstract

The application discloses a text regularization model training method and device, and a text regularization method and device. A specific embodiment of the text regularization model training method includes: sequentially inputting characters in the input character sequence corresponding to the input text into the neural network corresponding to the text regularization model to be generated, and the neural network corresponding to the text regularization model includes encoding For each character in the input character sequence, based on the state of the hidden layer in the decoder after decoding the last character input, use the encoder to encode to obtain the intermediate semantic vector of the character, and use the decoding The device interprets the intermediate semantic vector to obtain the prediction result of the character; according to the difference between the prediction result of the input character sequence and the labeling result corresponding to the input text, the parameters of the neural network are adjusted. This embodiment realizes the automatic training of the text regularization model, and improves the flexibility and accuracy of the text regularization model.

Description

technical field [0001] The present application relates to the field of computer technology, specifically to the field of speech synthesis technology, and in particular to a text regularization model training method and device, and a text regularization method and device. Background technique [0002] Artificial Intelligence (AI) is a new technical science that studies and develops theories, methods, technologies and application systems for simulating, extending and expanding human intelligence. Artificial intelligence is a branch of computer science that attempts to understand the essence of intelligence and produce a new intelligent machine that responds in a manner similar to human intelligence. Research in this field includes robotics, speech recognition, speech synthesis, Image recognition, natural language processing and expert systems, etc. Among them, speech synthesis technology is an important direction in the field of computer science and artificial intelligence. ...

AI Technical Summary

Problems solved by technology

However, the generalization of the rule-based method is poor, and there are strict restrictions on the context of the text. If the text format or content changes slightly, the corresponding rules may become invalid.

And with the increase of TTS requests, the diversity of each text changes, the number of rules gradually increases, and the maintenance of rules becomes more and more difficult, which is not conducive to saving resources

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