|TREND||DATASET||BEST METHOD||PAPER TITLE||PAPER||CODE||COMPARE|
In this paper we present DELTA, a deep learning based language technology platform.
#2 best model for Intent Detection on ATIS
Attention-based recurrent neural network models for joint intent detection and slot filling have achieved the state-of-the-art performance, while they have independent attention weights.
Building conversational systems in new domains and with added functionality requires resource-efficient models that work under low-data regimes (i. e., in few-shot setups).
Being able to recognize words as slots and detect the intent of an utterance has been a keen issue in natural language understanding.
SOTA for Intent Detection on SNIPS
Recently, data-driven task-oriented dialogue systems have achieved promising performance in English.
Spoken Language Understanding (SLU) mainly involves two tasks, intent detection and slot filling, which are generally modeled jointly in existing works.