The importance of fillers for text representations of speech transcripts

09/23/2020
by   Tanvi Dinkar, et al.
0

While being an essential component of spoken language, fillers (e.g."um" or "uh") often remain overlooked in Spoken Language Understanding (SLU) tasks. We explore the possibility of representing them with deep contextualised embeddings, showing improvements on modelling spoken language and two downstream tasks - predicting a speaker's stance and expressed confidence.

READ FULL TEXT

page 1

page 2

page 3

page 4

research
01/11/2020

Improving Spoken Language Understanding By Exploiting ASR N-best Hypotheses

In a modern spoken language understanding (SLU) system, the natural lang...
research
10/24/2022

Weak-Supervised Dysarthria-invariant Features for Spoken Language Understanding using an FHVAE and Adversarial Training

The scarcity of training data and the large speaker variation in dysarth...
research
12/13/2018

Coupled Representation Learning for Domains, Intents and Slots in Spoken Language Understanding

Representation learning is an essential problem in a wide range of appli...
research
12/15/2022

You were saying? – Spoken Language in the V3C Dataset

This paper presents an analysis of the distribution of spoken language i...
research
06/22/2023

Implicit spoken language diarization

Spoken language diarization (LD) and related tasks are mostly explored u...
research
10/30/2018

Spoken Language Understanding on the Edge

We consider the problem of performing Spoken Language Understanding (SLU...
research
10/31/2022

Design Considerations For Hypothesis Rejection Modules In Spoken Language Understanding Systems

Spoken Language Understanding (SLU) systems typically consist of a set o...

Please sign up or login with your details

Forgot password? Click here to reset