WAIS: Word Attention for Joint Intent Detection and Slot Filling
نویسندگان
چکیده
منابع مشابه
Attention-Based Recurrent Neural Network Models for Joint Intent Detection and Slot Filling
Attention-based encoder-decoder neural network models have recently shown promising results in machine translation and speech recognition. In this work, we propose an attention-based neural network model for joint intent detection and slot filling, both of which are critical steps for many speech understanding and dialog systems. Unlike in machine translation and speech recognition, alignment i...
متن کاملJoint Intent Detection and Slot Filling Using Convolutional Neural Networks
We describe a joint model for intent detection and slot filling based on convolutional neural networks (CNN). The proposed architecture can be perceived as a neural network (NN) version of the triangular CRF model (TriCRF), which exploits the dependency between intents and slots, and models them simultaneously. Our slot filling component is a globally normalized CRF style model (as opposed to l...
متن کاملA Joint Model of Intent Determination and Slot Filling for Spoken Language Understanding
Two major tasks in spoken language understanding (SLU) are intent determination (ID) and slot filling (SF). Recurrent neural networks (RNNs) have been proved effective in SF, while there is no prior work using RNNs in ID. Based on the idea that the intent and semantic slots of a sentence are correlative, we propose a joint model for both tasks. Gated recurrent unit (GRU) is used to learn the re...
متن کاملPosition-aware Attention and Supervised Data Improve Slot Filling
Organized relational knowledge in the form of “knowledge graphs” is important for many applications. However, the ability to populate knowledge bases with facts automatically extracted from documents has improved frustratingly slowly. This paper simultaneously addresses two issues that have held back prior work. We first propose an effective new model, which combines an LSTM sequence model with...
متن کاملA distant supervised learning system for the TAC-KBP Slot Filling and Temporal Slot Filling Tasks
This paper describes the system implemented by the NLP GROUP AT UNED for our first participation in the Knowledge Base Population at the Text Analysis Conference (TACKBP). For this Slot Filling Task, our approach was to design a distant supervised learning system, which was then specialized for the Regular Slot Filling and Full Temporal Slot Filling subtasks. From the initial Knowledge Base and...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Proceedings of the AAAI Conference on Artificial Intelligence
سال: 2019
ISSN: 2374-3468,2159-5399
DOI: 10.1609/aaai.v33i01.33019927