Conversation management method and system of outbound system, electronic equipment and storage medium
A dialogue management and pre-storage technology, applied in neural learning methods, telephone communication, electrical components, etc., can solve the problems that the outbound system cannot communicate with users in spoken language, and achieve the effects of humanized communication, labor cost saving, and flexible design
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Embodiment 1
[0068] This embodiment provides a dialog management method for an outbound call system. Such as figure 1 As shown, the dialogue management method of the outgoing call system of the present embodiment includes the following steps:
[0069] Step S101, acquiring semantic information;
[0070] Step S102, updating the current dialog state according to the semantic information;
[0071] Step S103, inputting the dialogue state into a pre-stored state machine to perform a state jump;
[0072]Step S104, the outbound call system outputs a question and answer according to the state after the state machine jumps. The dialog management method of the outbound system in this embodiment can realize oral communication between the user and the outbound system, and the outbound system can reply to the user's questions, realize humanized communication, improve user acceptance, and save a lot of labor costs for the enterprise. When the user side is an extension, the outbound call system of the...
Embodiment 2
[0074] On the basis of Embodiment 1, this embodiment provides a dialog management method for an outbound call system. Such as figure 2 As shown, after step S104, the dialog management method of the outbound call system of this embodiment further includes the following steps:
[0075] Step S201, after the state machine jumps to the preset state, input the semantic information into the pre-trained reinforcement learning model;
[0076] Step S202, the outbound call system outputs a question and answer according to the output result of the reinforcement learning model.
[0077] The dialogue management method of the outbound call system of this embodiment uses the trained reinforcement learning model for dialogue management, and uses the state machine to quickly collect man-machine dialogue data during the initial cold start of the dialogue for the training of the reinforcement learning model. In the hot start phase, switch to the reinforcement learning model for dialogue explor...
Embodiment 3
[0079] On the basis of Embodiment 2, this embodiment provides a dialog management method for an outbound call system. Such as image 3 As shown, before step S101, the dialog management method of the outbound call system of this embodiment also includes the following steps:
[0080] Step S100, acquiring slot information in domain information, which is used to form a dialog state;
[0081] Divide according to different fields, and determine the information that needs to be obtained according to the field information. For example, for the common order confirmation field in the OTA industry, the OTA manufacturer in this field confirms to the hotel whether an order can be accepted, and extracts the slot information that needs to be obtained, such as : Can be determined, if not sure, extract the reason. According to the slot information, the robot's actions are targeted. For example, if the acquired slot information includes "sure", "full room", "not cooperative", etc., the robot ...
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