Abstract: There is disclosed a method and system for processing a user spoken utterance, the method comprising: receiving, from a user, an indication of the user spoken utterance; generating, a text representation hypothesis based on the user spoken utterance; processing, using a first trained scenario model and a second trained scenario model, the text representation hypothesis to generate a first scenario hypothesis and a second scenario hypothesis, respectively; the first trained scenario model and the second trained scenario model having been trained using at least partially different corpus of texts; analyzing, using a Machine Learning Algorithm (MLA), the first scenario hypothesis and the second scenario hypothesis to determine a winning scenario having a higher confidence score; based on the winning scenario, determining by an associated one of the first trained scenario model and the second trained scenario model, an action to be executed by the electronic device; executing the action.

Abstract: There is disclosed a method and system for processing a user spoken utterance, the method comprising: receiving, from a user, an indication of the user spoken utterance; generating, a text representation hypothesis based on the user spoken utterance; processing, using a first trained scenario model and a second trained scenario model, the text representation hypothesis to generate a first scenario hypothesis and a second scenario hypothesis, respectively; the first trained scenario model and the second trained scenario model having been trained using at least partially different corpus of texts; analyzing, using a Machine Learning Algorithm (MLA), the first scenario hypothesis and the second scenario hypothesis to determine a winning scenario having a higher confidence score; based on the winning scenario, determining by an associated one of the first trained scenario model and the second trained scenario model, an action to be executed by the electronic device; executing the action.