A survey of joint intent detection and slot filling models in natural language understanding

H Weld, X Huang, S Long, J Poon, SC Han - ACM Computing Surveys, 2022 - dl.acm.org
Intent classification, to identify the speaker's intention, and slot filling, to label each token
with a semantic type, are critical tasks in natural language understanding. Traditionally the …

Using VADER sentiment and SVM for predicting customer response sentiment

A Borg, M Boldt - Expert Systems with Applications, 2020 - Elsevier
Customer support is important to corporate operations, which involves dealing with
disgruntled customer and content customers that can have different requirements. As such, it …

Systematic review on chatbot techniques and applications

DM Park, SS Jeong, YS Seo - Journal of Information Processing …, 2022 - koreascience.kr
Chatbots were an important research subject in the past. A chatbot is a computer program or
an artificial intelligence program that participates in a conversation via auditory or textual …

Natural language understanding approaches based on joint task of intent detection and slot filling for IoT voice interaction

P Ni, Y Li, G Li, V Chang - Neural Computing and Applications, 2020 - Springer
Abstract Internet of Things (IoT) based voice interaction system, as a new artificial
intelligence application, provides a new human–computer interaction mode. The more …

Implementation of a machine learning algorithm for automated thematic annotations in avatar: A linear support vector classifier approach

A Hudon, M Beaudoin… - Health Informatics …, 2022 - journals.sagepub.com
Avatar Therapy (AT) is a modern therapeutic alternative for patients with schizophrenia
suffering from persistent auditory verbal hallucinations. Its intrinsic therapeutical process is …

Stacked DeBERT: All attention in incomplete data for text classification

GC Sergio, M Lee - Neural Networks, 2021 - Elsevier
In this paper, we propose Stacked DeBERT, short for Stacked Denoising Bidirectional
Encoder Representations from T ransformers. This novel model improves robustness in …

HyperEmbed: Tradeoffs between resources and performance in NLP tasks with hyperdimensional computing enabled embedding of n-gram statistics

P Alonso, K Shridhar, D Kleyko… - … Joint Conference on …, 2021 - ieeexplore.ieee.org
Recent advances in Deep Learning have led to a significant performance increase on
several NLP tasks, however, the models become more and more computationally …

End to end binarized neural networks for text classification

K Shridhar, H Jain, A Agarwal… - Proceedings of SustaiNLP …, 2020 - aclanthology.org
Deep neural networks have demonstrated their superior performance in almost every
Natural Language Processing task, however, their increasing complexity raises concerns. A …

Transformer-capsule model for intent detection (student abstract)

A Obuchowski, M Lew - Proceedings of the AAAI conference on artificial …, 2020 - aaai.org
Intent recognition is one of the most crucial tasks in NLU systems, which are nowadays
especially important for designing intelligent conversation. We propose a novel approach to …

Reinforcement learning over knowledge graphs for explainable dialogue intent mining

K Yang, X Kong, Y Wang, J Zhang, G De Melo - IEEE Access, 2020 - ieeexplore.ieee.org
In light of the millions of households that have adopted intelligent assistant powered
devices, multi-turn dialogue has become an important field of inquiry. Most current methods …