ConQX: Semantic Expansion of Spoken Queries for Intent Detection based on Conditioned Text Generation

09/02/2021
by   Eyup Halit Yilmaz, et al.
7

Intent detection of spoken queries is a challenging task due to their noisy structure and short length. To provide additional information regarding the query and enhance the performance of intent detection, we propose a method for semantic expansion of spoken queries, called ConQX, which utilizes the text generation ability of an auto-regressive language model, GPT-2. To avoid off-topic text generation, we condition the input query to a structured context with prompt mining. We then apply zero-shot, one-shot, and few-shot learning. We lastly use the expanded queries to fine-tune BERT and RoBERTa for intent detection. The experimental results show that the performance of intent detection can be improved by our semantic expansion method.

READ FULL TEXT

page 1

page 2

page 3

page 4

research
04/04/2020

CG-BERT: Conditional Text Generation with BERT for Generalized Few-shot Intent Detection

In this paper, we formulate a more realistic and difficult problem setup...
research
08/13/2021

GQE-PRF: Generative Query Expansion with Pseudo-Relevance Feedback

Query expansion with pseudo-relevance feedback (PRF) is a powerful appro...
research
04/17/2021

Multilingual and Cross-Lingual Intent Detection from Spoken Data

We present a systematic study on multilingual and cross-lingual intent d...
research
11/03/2020

Conditioned Text Generation with Transfer for Closed-Domain Dialogue Systems

Scarcity of training data for task-oriented dialogue systems is a well k...
research
10/22/2017

Bringing Semantic Structures to User Intent Detection in Online Medical Queries

The Internet has revolutionized healthcare by offering medical informati...
research
09/07/2023

All Labels Together: Low-shot Intent Detection with an Efficient Label Semantic Encoding Paradigm

In intent detection tasks, leveraging meaningful semantic information fr...
research
12/16/2020

Query expansion with artificially generated texts

A well-known way to improve the performance of document retrieval is to ...

Please sign up or login with your details

Forgot password? Click here to reset