Voice Quality Assessment by Simulating GRBAS Scoring

Chaitanya Gadepalli, Farideh Jalali-najafabadi, Zheng Xie, Barry Cheetham, Jarrod Homer

Research output: Chapter in Book/Conference proceedingConference contributionpeer-review

Abstract

This paper is about the assessment of voice quality as required routinely in hospital voice clinics. It describes a computer application capable of analysing recordings of a patient's voice and producing quantitative assessments of its quality, simulating those traditionally made by trained speech and language therapists (SLTs). Adopting a machine learning approach based on a database of recordings and assessments by a team of SLTs required measurements of consistency to be taken into account. The means of doing this, details of the machine learning approaches and the performance of the resulting algorithms are presented.
Original languageEnglish
Title of host publication 2017 European Modelling Symposium (EMS)
PublisherIEEE
DOIs
Publication statusPublished - 2017
Event2017 European Modelling Symposium - Jurys Inn Manchester Great Bridgewater Street, Manchester, United Kingdom
Duration: 20 Nov 201721 Nov 2017

Conference

Conference2017 European Modelling Symposium
Abbreviated titleEMS 2017
Country/TerritoryUnited Kingdom
CityManchester
Period20/11/1721/11/17

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