Abstract: With the widespread adoption of smart homes, users have gradually become accustomed to controlling multiple devices or functions through a single command. Traditional single-intent recognition dialogue systems cannot parse these complex commands, resulting in a stiff interaction process and poor user experience. To address this issue, Proposes a multi-module cascade multi-intent parsing dialogue system. This system first uses an intent segmentation model to split the user's multi-intent request into single-intent requests; then, it extracts the single-intent categories through a two-level classification model, including coarse-grained intent classification and fine-grained intent classification; finally, the dialogue management module completes the domain and slot information based on preset rules. The system's performance was evaluated using data from six types of home appliances. The basic command accuracy rate for each module and the overall system reached 100%, and the generalized command accuracy rate exceeded 96%, meeting the needs of practical applications.

Key words: Smart home, Voice interaction, Dialogue system, Text classification, Dialogue management