De grootste kennisbank van het HBO

Inspiratie op jouw vakgebied

Vrij toegankelijk

Terug naar zoekresultatenDeel deze publicatie

Determining the ideal length of spontaneous speech fragments for predictive analysis

Poster

Open access

Rechten:Alle rechten voorbehouden

Determining the ideal length of spontaneous speech fragments for predictive analysis

Poster

Open access

Rechten:Alle rechten voorbehouden

Samenvatting

Spontaneous speech is an important source of information for aphasia research. It is essential to collect the right amount of data: enough for distinctions in the data to become meaningful, but not so much that the data collection becomes too expensive or places an undue burden on participants. The latter issue is an ethical consideration when working with participants that find speaking difficult, such as speakers with aphasia. So, how much speech data is enough to draw meaningful conclusions? How does the uncertainty around the estimation of model parameters in a predictive model vary as a function of the length of texts used for training?

Trefwoorden
OrganisatieHogeschool Utrecht
AfdelingKenniscentrum Digital Business & Media
LectoraatArtificial Intelligence
Jaar2019
TypeConferentiebijdrage
DOI10.6084/m9.figshare.9876383.v1
TaalEngels

Op de HBO Kennisbank vind je publicaties van 26 hogescholen

De grootste kennisbank van het HBO

Inspiratie op jouw vakgebied

Vrij toegankelijk