Spoken Language Understanding: Recent Advances and Future Direction

Australia Deep Learning NLP Group

Spoken Language Understanding: Recent Advances and Future Direction

AJCAI 2022 Tutorial

Organised by The University Of Sydney, The University Of Western Australia

Time and Location

1.30pm – 4.30pm (UTC/GMT+8, AWST) on Monday, 05 December 2022

Resource

Abstract

When a human speaks to a machine how does the latter elicit meaning from the communication? This is an important AI task as it enables the machine to construct a sensible answer or perform a useful action for the human. Meaning is represented at the sentence level, identification of which is known as intent detection, and at the word level, a labelling task called slot filling. This dual level joint task requires innovative thinking about natural language and deep learning network design and as a result many approaches have been tried.

In this tutorial we will discuss how the joint task is set up and introduce Spoken Language Processing (NLP) and Deep Learning basics. We will cover the datasets, experiments and metrics used in the field. We will describe how the machine uses the latest NLP and Deep Learning techniques to address the task, including recurrent and non-recurrent (attention based Transformer) networks and pre-trained models (e.g. BERT). We will then look in detail at a network that allows the two levels of the task to explicitly interact to boost performance. We will do a code walk through of a Python notebook for this model and attendees will have an opportunity to do some light coding tasks on this model to further their understanding.

Tutorial Outline

Time Topic
13:30 - 14:00 Introduction to the NLP and SLU
14:00 - 14:30 Joint SLU Approaches
14:30 - 14:45 QnA and Break
14:45 - 15:00 Hands-on Exercise (Joint BERT)
15:00 - 15:15 SLU Evaluation
15:15 - 16:00 Hands-on Exercise (Datasets, Metrics, Experiments)
16:00 - 16:15 Future Direction
16:15 - 16:30 QnA

Organisers/Presenters

Reference