Method for verifying semantic consistency of land-air conversation based on improved LSTM-RNN

A technology of land-to-air communication and verification methods, which is applied in semantic analysis, natural language data processing, special data processing applications, etc., can solve the problem that the matching accuracy rate is less than 85%, and achieve suppression of overfitting, expression balance, The effect of improving the accuracy of calibration

Inactive Publication Date: 2018-09-11
CIVIL AVIATION UNIV OF CHINA
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We also applied LSTM-RNN and RNN models to the semantic matching

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  • Method for verifying semantic consistency of land-air conversation based on improved LSTM-RNN
  • Method for verifying semantic consistency of land-air conversation based on improved LSTM-RNN
  • Method for verifying semantic consistency of land-air conversation based on improved LSTM-RNN

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[0049] The LSTM-RNN-based aeronautical radio communication semantic consistency verification method provided by the present invention will be described in detail below in conjunction with the accompanying drawings and specific embodiments.

[0050] like figure 1 Shown, the ground-air conversation semantics consistency check method based on improved LSTM-RNN provided by the present invention comprises the following steps carried out in order:

[0051] Step 1) Make a corpus:

[0052] Step 1.1) From the actual land-air call, relevant teaching materials and the Civil Aviation Administration's land-air call standard, select the sentence pair of the echo type and store it in the txt text;

[0053]Step 1.2) Divide the sentence pairs in the above text into two types: positive samples and negative samples, wherein positive samples are composed of semantically consistent sentence pairs, and negative samples are composed of semantically inconsistent sentence pairs;

[0054] Step 1.3) c...

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Abstract

The invention discloses a method for verifying the semantic consistency of land-air conversation based on improved LSTM-RNN. The method comprises the steps: making a corpus: making a special vocabulary according to the conversation standard and the corpus of the civil aviation and obtaining a one-hot vector of the words: generating a semantic vector of two sentences in each sentence pair; processing the semantic vectors through an average pooling method and inputting the processed semantic vector into an MLP model; learning the degree of correlation between two semantic vectors through the MLP; determining the consistency of semantics through KNN. An original method for processing a sequence based on LSTM-RNN is lower in verification precision even if preventing the gradient of an independent RNN algorithm from disappearing. The method provided by the invention employs the average pooling method for preventing the overfitting phenomenon, innovatively employs the MLP for the computing,and enables the model to be more complete in the learning degree of the correlation. Because a model in deep learning is used for automatically learning the sample features, the method does not need the statistical analysis of mass data.

Description

technical field [0001] The invention belongs to the technical field of semantic consistency verification of land and air calls in civil aviation transportation, and in particular relates to a semantic consistency verification method for land and air calls based on improved LSTM-RNN. Background technique [0002] In the field of civil aviation, aviation radiotelephone communication between controllers and pilots is very important, and it can be said that it is closely related to the safety of aircraft. Because of land-air communication errors, many air accidents have been caused. With the advancement of science and technology, although the land and air communication errors caused by equipment and hardware have been greatly reduced, communication errors caused by human factors such as controllers or pilots working for a long time, fatigue, mental stress, and excessive pressure occur from time to time . Therefore, using artificial intelligence-related theories and technologie...

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Application Information

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IPC IPC(8): G06N3/04G06F17/27
CPCG06N3/049G06F40/242G06F40/284G06F40/30
Inventor 贾桂敏程方圆杨金锋
Owner CIVIL AVIATION UNIV OF CHINA
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