Skip to main navigation
Skip to search
Skip to main content
Teesside University's Research Portal Home
Search content at Teesside University's Research Portal
Home
Profiles
Research units
TeesRep
Student theses
Projects
Datasets
Equipment
Press/Media
Automatic Accent and Gender Recognition of Regional UK Speakers
Chrisina Jayne
, Victor Chang
, Jozeene Bailey
, Qianwen Ariel Xu
Centre for Digital Innovation
School of Computing, Engineering & Digital Technologies
Research output
:
Chapter in Book/Report/Conference proceeding
›
Conference contribution
54
Downloads (Pure)
Overview
Fingerprint
Fingerprint
Dive into the research topics of 'Automatic Accent and Gender Recognition of Regional UK Speakers'. Together they form a unique fingerprint.
Sort by
Weight
Alphabetically
Keyphrases
Voice Sample
100%
United Kingdom
50%
Audio
50%
Electronic Commerce
50%
Support Vector Machine
50%
Artificial Neural Network
50%
Network Support
50%
Machine Learning Classifiers
50%
Random Forest
50%
K-nearest
50%
Service Industry
50%
Sampling Methods
50%
Geographical Origin
50%
Voice Assistant
50%
Automated Recognition
50%
Pronunciation
50%
Regional Dialects
50%
Regional Accent
50%
NLP.
50%
Speech Recognition
50%
British Isles
50%
Computer Science
Neural Network
100%
Support Vector Machine
100%
Random Decision Forest
100%
Speech Recognition
100%
k-Nearest Neighbors Algorithm
100%
Voice Assistant
100%
Machine Learning
100%
Learning System
100%