Pinyin-based dialogue system text error correction system and method

A dialogue system and text error correction technology, which is applied in the field of pinyin-based dialogue system text error correction system, can solve the problems of long training time, increased error correction cost, and poor migration, so as to achieve simple algorithm implementation and improve error correction accuracy , The effect of reducing the cost of error correction

Active Publication Date: 2019-11-01
深思考人工智能机器人科技(北京)有限公司
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AI Technical Summary

Problems solved by technology

[0005] However, using the deep learning model to correct the text of the dialogue system based on Pinyin also requires a large amount of data for training, which takes a long time and is not easy to implement, which increases the cost of error correction
In addition, the trained deep learning model performs error correction on the text of the dialogue system based on Pinyin in a certain field during training. When the deep learning module is transferred and applied to the text of the dialogue system based on Pinyin in another field, then The accuracy of error correction will be greatly reduced, that is, the migration of the error correction of the text of the dialogue system based on Pinyin using the deep learning model is poor

Method used

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  • Pinyin-based dialogue system text error correction system and method
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  • Pinyin-based dialogue system text error correction system and method

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Embodiment Construction

[0042] In order to make the object, technical solution and advantages of the present invention clearer, the present invention will be further described in detail below with reference to the accompanying drawings and examples.

[0043] In order to improve the accuracy of error correction on the basis of reducing the cost of error correction, the embodiment of the present invention adopts the text fuzzy matching strategy (TFM, TextFuzzy Matching ) after matching the abnormal information with the set information list, the matched information is obtained, and the set Pinyin-based text similarity algorithm (PTS, Pinyin-Based Text Similarity) is used to calculate the similarity between the abnormal information and the obtained matching information, Get the information with the highest similarity, and correct the abnormal information.

[0044] Since the PTS set fully considers that speech recognition uses sound signals as input, the text similarity judgment is based on pinyin, and th...

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Abstract

The invention discloses a pinyin-based dialogue system text error correction system and a pinyin-based dialogue system text error correction method. According to the embodiment of the invention, afterabnormal information is detected in a dialogue system text based on pinyin, the abnormal information is matched with a set information list by adopting a set text fuzzy matching strategy (TFM), and then matched information is obtained; and similarity calculation is performed on the abnormal information and the obtained matched information through adoption of the set Pinyin-based text similarity algorithm (PTS) to obtain information with the highest similarity, and the abnormal information is corrected. According to the embodiments of the invention, the error correction accuracy is improved onthe basis of reducing the error correction cost.

Description

technical field [0001] The invention relates to language processing technology in the field of computers, in particular to a text error correction system and method of a dialogue system based on pinyin. Background technique [0002] Correcting speech errors based on speech recognition results is an important task in the speech understanding process. Due to the limitation of the accuracy of speech recognition, errors often occur in the results of speech recognition, which will hinder the follow-up work of speech understanding and increase the difficulty of speech understanding. [0003] When correcting the dialogue text based on pinyin, it is divided into two steps, the first step is error detection, and the second step is error correction. Among them, the commonly used methods for error detection include maximum entropy, n-gram speech model, etc., and error correction uses perplexity sets or language models to selectively replace detected errors. [0004] With the developm...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F17/27G06F16/332
CPCG06F16/3329Y02D10/00
Inventor 杨志明
Owner 深思考人工智能机器人科技(北京)有限公司
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