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

Active Publication Date: 2021-06-11
深圳奇实科技有限公司
View PDF8 Cites 0 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0006] The present invention provides an automatic speech recognition method and system based on artificial intelligence to solve the probl

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Automatic speech recognition method and system based on artificial intelligence
  • Automatic speech recognition method and system based on artificial intelligence
  • Automatic speech recognition method and system based on artificial intelligence

Examples

Experimental program
Comparison scheme
Effect test

Example Embodiment

[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...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

PUM

No PUM Login to view more

Abstract

The invention discloses an automatic speech recognition method and system based on artificial intelligence. The method comprises the steps: comparing vocabularies in a recognition result with professional vocabularies in a vocabulary classification template by employing the vocabulary classification template, acquiring the proportion of the professional vocabularies in the vocabularies in the recognition result, and judging whether professional vocabulary speech recognition is needed or not according to the proportion. According to the scheme provided by the invention, the accuracy and accuracy of the recognition of the professional vocabularies can be improved, particularly the accuracy, precision and specialty of video conference records in the professional field are enhanced, and the specialty of enterprises in the related professional field is improved, More importantly, misunderstanding of vocabulary recognition caused by automatic voice recognition of professional vocabularies is reduced, and heavy loss caused by misunderstanding of voice recognition is prevented. Meanwhile, on the basis of the vocabulary classification template, the search rate of the professional vocabularies is improved, and then the recognition efficiency of the automatic voice for the professional vocabulary is improved.

Description

technical field [0001] The invention relates to the technical field of artificial intelligence, in particular to an artificial intelligence-based automatic speech recognition method and system. Background technique [0002] Automatic Speech Recognition (ASR for short) is a technology for converting human speech into text. Speech recognition is a multidisciplinary field, which is closely connected with many disciplines such as acoustics, phonetics, linguistics, digital signal processing theory, information theory, and computer science. Due to the diversity and complexity of speech signals, speech recognition systems can only obtain satisfactory performance under certain restrictions, or can only be applied to certain specific occasions. [0003] The goal of automatic speech recognition technology is to enable computers to "dictate" continuous speech spoken by different people, which is commonly known as "voice dictation machine", which is a technology that realizes the conve...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

Application Information

Patent Timeline
no application Login to view more
IPC IPC(8): G10L15/26G10L15/02G10L15/16G10L15/06G10L15/08G10L15/18G10L21/0208G10L25/57
CPCG10L15/26G10L15/02G10L15/16G10L15/063G10L15/08G10L15/18G10L21/0208G10L25/57G10L2015/0631G10L2015/0633
Inventor 张子奇聂鹏
Owner 深圳奇实科技有限公司
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Try Eureka
PatSnap group products