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A method of voice navigation robot based on deep learning

A technology of deep learning and voice navigation, applied in the field of telecommunications, can solve the problems of complex unstructured text content, a large number of manual tagging keywords, and the consumption of large human resources, so as to improve labor costs, improve recognition accuracy, and save human effect

Active Publication Date: 2021-08-17
广州云趣信息科技有限公司
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AI Technical Summary

Problems solved by technology

Better results can be obtained by using the traditional rule method, but a lot of manual labor is required to label keywords and maintain the keyword thesaurus in the later stage
However, since 20,000 to 30,000 users use voice navigation robots every day, the unstructured text content becomes complicated, which requires a lot of manual annotation and establishment of a keyword vocabulary, which will consume a lot of human resources. It also requires a lot of time cost

Method used

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  • A method of voice navigation robot based on deep learning
  • A method of voice navigation robot based on deep learning
  • A method of voice navigation robot based on deep learning

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Embodiment Construction

[0031] The present invention will be further described in conjunction with the following application scenarios.

[0032] see figure 1 , which shows a method for implementing a voice-guided robot based on deep learning, including:

[0033] Obtain training corpus: Obtain training call recording text data to form a training corpus, where training call recording text data includes call recording text and corresponding navigation queue labels.

[0034] Data preprocessing: Preprocessing the training call recording text data to obtain standardized training corpus.

[0035] Optionally, after the call recording text is obtained, the text is preprocessed, so as to complete the normalization of the training corpus.

[0036] Optionally, preprocessing the training call recording text data includes the following steps:

[0037] 1) Filter phrases: Filter the sentences whose sentence length is lower than the threshold in the training call recording text.

[0038] 2) Text word segmentation...

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Abstract

The invention provides a method for implementing a voice navigation robot based on deep learning. The method includes the steps of: obtaining user call text data; inputting the user call text into a trained navigation queue classification model based on deep learning for prediction and recognition, and obtaining the output Navigation queue prediction result; according to the obtained navigation queue prediction result, the user is transferred to the corresponding manual queue for processing. The method provided by the invention can perform targeted training on a large amount of text data, and can quickly obtain good results. When new knowledge is encountered in the later stage, training can be strengthened to adapt the model to the new knowledge existing in the text data, which can greatly improve labor costs and increase time costs.

Description

technical field [0001] The present invention relates to the fields of telecommunication, deep learning and natural language, and in particular to a method for implementing a navigation robot based on deep learning for operator texts. Background technique [0002] At present, the voice navigation robot uses the voice interaction method to identify the user's intention, and then the robot automatically judges the user's situation and docks with the relevant manual queue for processing. This process requires the robot to automatically identify the user's speech information and then transfer to the relevant queue. Better results can be obtained by using traditional rules, but a lot of manual labor is required to label keywords and maintain the keyword thesaurus later. However, since 20,000 to 30,000 users use voice navigation robots every day, the unstructured text content becomes complicated, which requires a lot of manual annotation and establishment of a keyword vocabulary, ...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06F40/279G06F40/289G06N3/04G10L15/26B25J11/00
CPCG06F40/279G06F40/289G10L15/26B25J11/0005G06N3/045
Inventor 黄诗雅罗睦军邓从健
Owner 广州云趣信息科技有限公司
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