Man-machine dialogue anomaly detection system and method

A technology of anomaly detection and man-machine dialogue, applied in the field of information processing

Active Publication Date: 2017-01-11
AISPEECH CO LTD
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0008] Aiming at the above-mentioned deficiencies in the prior art, the present invention proposes a human-machine dialogue abnormality detection system and method, which can adjust the reply strategy and content when it is detected that the machine cannot normally reply to the user (that is, an abnormality occurs), so as to complete the dialogue Task

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  • Man-machine dialogue anomaly detection system and method

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Embodiment Construction

[0024] like figure 1 As shown, the present embodiment relates to a human-machine dialog anomaly detection system, comprising: a speech recognition module (ASR module), a speech synthesis module (TTS module), a semantic recognition module (SLU module), and a dialog state tracking module (DST module) , dialog decision module (DM module), database query module (DATA module), natural language generation module (NLG module), abnormality detection module (DAD module) and exception processing module, wherein: ASR module unifies user input into character data Output to the SLU module. The SLU module extracts the semantics in the character data and then outputs the extraction result to the DST module. The DST module estimates the user's intention based on the dialogue above and sends the most likely user intention to the DATA module for database query. DATA The module returns the result of the query to the DST module, and the DST module sends the estimated user intent and database quer...

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Abstract

Provided is a man-machine dialogue anomaly detection system and method. The method includes steps: acquiring and marking historical dialogue data, training an anomaly detection model by employing the marked data, conducting anomaly detection by employing the trained anomaly detection model when receiving real-time dialogue data, and obtaining a result. The system comprises an automatic speech recognition module (ASR module), a text-to-speech module (TTS module), a spoken language understanding module (SLU module), a dialogue state tracking module (DST module), a dialogue management module (DM module), a database query module (DATA module), a natural language generation module (NLG module), and an anomaly detection and processing module. According to the system and method, replies given by a machine can be reliable, and the system and method can be applied to any scene.

Description

technical field [0001] The present invention relates to a technology in the field of information processing, in particular to a system and method for detecting anomalies in man-machine dialogue. Background technique [0002] Since the advent of Siri on iPhone4s and iPad3, the human-computer dialogue system has quickly attracted the attention of the public, from curiosity, trial, and teasing at the beginning, to disappointment and abandonment after being unable to answer questions or answering questions that are not what they asked. Although the experience is unsatisfactory, Siri’s fierce market response after its launch reflects the high expectations of the public for artificial intelligence. International giants such as Apple, Google, Microsoft, and Amazon have invested a lot of resources in researching products similar to Siri. [0003] The core of the human-machine dialogue system is that the machine can automatically understand and analyze the questions raised by the use...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G10L25/27G10L25/30G10L15/22
CPCG10L15/22G10L25/27G10L25/30
Inventor 俞凯曹迪陈露郑达
Owner AISPEECH CO LTD
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