Voice dialogue processing method and apparatus

A computer-implemented voice dialogue processing method involving at least a voice customer service server and a dialogue flow design server, wherein the voice customer service server comprises at least an Automatic Speech Recognition (ASR) module, a Natural Language Understanding (NLU) module, a Natural Language Generation (NLG) module, a Text To Speech (TTS) module, and a dialogue management engine, the method comprising:

• obtaining, by the dialogue flow design server, a dialogue flow design request from a dialogue flow design client, and determining at least one dialogue flow corresponding to the dialogue flow design request, wherein the dialogue flow comprises a plurality of dialogue nodes having a set order, the dialogue nodes further includes a phrase that the dialogue node replies to the user, a list of intents used to parse the user voice, and a jump logic;
• and wherein the dialogue flow design request is generated by drawing a plurality of dialogue flows for one dialogue project on the dialogue flow design client by a voice business personnel of the provider;
• generating, by the dialogue flow design server, a dialogue business customization file by parsing the at least one dialogue flow to automatically identify a node content and node type of each ordered node in the at least one dialogue flow, the dialogue business customization file being a JSON file;
• sending, by the dialogue flow design server, the dialogue business customization file to a voice customer service server,
• loading the dialogue business customization file by the dialogue management engine of the voice customer service server;
• generating a training sample set for the dialogue management engine based on the dialogue business customization file and then training the dialogue management engine using the training sample set, by the voice customer service server;
• performing speech recognition and semantic understanding on a user voice to be processed, by the ASR module and the NLU module of the voice customer service server, to determine corresponding voice semantics;
• determining a reply sentence for the voice semantics, by the voice customer service server, based on the trained dialogue management engine of the voice customer service server;
• and
• performing natural language generation and speech synthesis on the determined reply sentence, by the NLG module and the TTS module of the voice customer service server, to generate a customer service voice for replying to the user voice.