SPEECH RECOGNITION METHOD FOR HUMAN-MACHINE INTERACTION OF SMART APPARATUS, AND SYSTEM

摘要

A speech recognition method for human-machine interaction of a smart apparatus and a system, pertaining to the technical field of speech recognition, and improving the accuracy of speech recognition by means of joint optimization training of intent detection and slot filling. The method comprises: performing word segmentation on speech data of a user's question to obtain an original word sequence, and generating a vector representation of the original word sequence by means of embedding processing; performing weighting processing on a hidden state vector h_i and a slot context vector c_i^S to obtain a slot label model y_i^S; performing weighting processing on a hidden state vector hT and an intent context vector c^I to obtain an intent prediction model y^I; joining the slot context vector c_i^S and the intent context vector c^I by means of a slot gate g, and obtaining a transformed representation of the slot label model y_i^S by means of the slot gate g; and constructing an objective function for joint optimization of the intent prediction model y^I and the transformed slot label model y_i^S, and performing intent detection on the speech data of the user's question on the basis of the objective function.