Jun 29, 2021 · This paper presents a few-shot spoken intent classification approach with task-agnostic representations via meta-learning paradigm. Specifically ...
This paper brings the meta-learning paradigm to few-shot speech to intent classifica- tion task. We show on two popular spoken intent detection datasets: the ...
This paper uses the popular representation-based meta-learning learning to build a task-agnostic representation of utterances, that then use a linear ...
Contains the meta-learning splits for Google Speech Commands and Fluent.AI Dataset used in representation based meta-learning for few-shot spoken intent ...
A recent development of deep learning has revolutionized various audio-based applications such as emotion recognition (ER) [1], environmental sound ...
Using few-shot spoken intent recognition a user can add new commands “move” to the voice assistant with a small amount of labeled training data. Why ...
Bibliographic details on Representation based meta-learning for few-shot spoken intent recognition.
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This paper introduces a novel dataset for multimodal intent recognition (MIntRec) to address this issue.
In this paper, we introduce a contrastive learning-based task adaptation model (CTA) for the task of few-shot intent recognition.