Automatic speech recognition method and automatic speech recognition system based on artificial intelligence

Abstract

The invention discloses an automatic speech recognition method and an automatic speech recognition system based on artificial intelligence. The system mainly comprises four modules of a speech preprocessing module, a speech feature extraction module, a speech training recognition module and a text correction module. According to the system, the speech training recognition module is adopted to learn the speech features and speech corresponding character codes, firstly, convolution learning of frequency spectrum characteristics is carried out through a feature learning layer, then the semantic information among the frequency spectrum features is learned through a semantic learning layer, finally, the comprehensively learned information is decoded through an output layer, and a correspondingtext is output. Therefore, a Chinese character mapping table is directly used for encoding and decoding labels, phoneme encoding and decoding of the text are not needed, then the text is decoded intothe text, and the training process is simplified.

Description

technical field [0001] The invention relates to the technical field of speech recognition in artificial intelligence, in particular to an automatic speech recognition technology based on artificial intelligence. Background technique [0002] Artificial Intelligence (AI for short) 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, computer vision, natural language processing and expert systems, etc. [0003] The development of existing automatic speech recognition technology mainly tends to two stages of training and decoding; training, that is, training the acoustic model through a large amount...

AI Technical Summary

Problems solved by technology

However, there are thousands of common words in any language, and learning thousands of models requires not only a huge corpus, but also a long iteration time

In addition, Chinese is also divided into tonal and non-tonal characters, homophones, etc., resulting in a multiplied number of models

This has brought a lot of inconvenience to users, making speech recognition technology unable to be industrialized on a large scale

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