Machine learning model training method, intention recognition method, related device and equipment

Abstract

The embodiment of the invention discloses a machine model training method, an intention recognition method and related devices in the field of artificial intelligence. The method comprises the following steps: training a capsule network model according to a training sample, wherein the training process comprises the steps of iteratively adjusting a current weight coefficient corresponding to a first prediction vector according to the similarity between a first activation vector and the first prediction vector, wherein the first activation vector is the weighted sum of a plurality of predictionvectors, and represents the probability that the intention of the training text is predicted as a first real intention; and the first prediction vector represents a contribution of the first semanticfeature to the first real intent. Furthermore, the weight coefficient corresponding to the prediction vector with the large similarity with the first activation vector is increased; therefore, the semantic features corresponding to the prediction vectors with the large similarity with the first activation vectors are screened out, the semantic features corresponding to the prediction vectors withthe small similarity with the first activation vectors are filtered out, the semantic features with the high correlation degree are screened out to form the intention, and the accuracy of intention recognition of the model is improved.

Description

technical field [0001] The present application relates to the technical field of machine learning, and in particular to a training method of a capsule network model for recognizing intent, a training method of a combined machine learning model for recognizing intent, an intent recognition method, and related devices and equipment. Background technique [0002] With the development of artificial intelligence technology, dialogue systems have been applied to more and more electronic devices, such as mobile phones, smart assistants, smart speakers, smart vehicle equipment, smart robots, etc. The dialogue system provides users with an interactive way to directly talk to the machine through voice, which is more convenient and flexible than traditional click or touch methods. In the process of interacting with the machine through dialogue, accurately identifying the intention behind the user's utterance is the key to the correct execution of the dialogue process. If the intent re...

AI Technical Summary

Problems solved by technology

By applying the machine learning model, this method has better generalization ability, does not need to enumerate all possible statements, and can directly predict the category of intent classification, but the accuracy of intent recognition is poor

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