MASSIVE is a parallel dataset of > 1M utterances across 51 languages with annotations for the Natural Language Understanding tasks of intent prediction and slot annotation. Utterances span 60 intents and include 55 slot types. MASSIVE was created by localizing the SLURP dataset, composed of general Intelligent Voice Assistant single-shot interactions.
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For the purpose of training and evaluating our intent classification model for electric automation, we curated a dataset consisting of intent-based user instructions. The dataset comprises a total of 14 intents, each associated with approximately 10 user instructions, resulting in a total of 140 instructions for electric automation. The intents were carefully selected to cover a diverse range of control commands and actions commonly encountered in electric automation scenarios. These intents include commands for turning on/off electrical appliances. Each user instruction in the dataset is labeled with its corresponding intent, allowing the model to learn the mapping between input instructions and their intended actions.
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