Domain Adaptation with Clustered Language Models
| dc.creator | Ueberla, Joerg P. | |
| dc.date | 1997-03-04 | |
| dc.date.accessioned | 2026-07-07T09:10:44Z | |
| dc.date.available | 2026-07-07T09:10:44Z | |
| dc.description | In this paper, a method of domain adaptation for clustered language models is developed. It is based on a previously developed clustering algorithm, but with a modified optimisation criterion. The results are shown to be slightly superior to the previously published 'Fillup' method, which can be used to adapt standard n-gram models. However, the improvement both methods give compared to models built from scratch on the adaptation data is quite small (less than 11% relative improvement in word error rate). This suggests that both methods are still unsatisfactory from a practical point of view. | |
| dc.description | preprint - to appear in ICASSP 97 | |
| dc.identifier | https://arxiv.org/abs/cmp-lg/9703001 | |
| dc.identifier | http://arxiv.org/abs/cmp-lg/9703001 | |
| dc.identifier.uri | http://salesiana.dossiersoluciones.com/handle/123456789/151438 | |
| dc.subject | Computation and Language | |
| dc.title | Domain Adaptation with Clustered Language Models | |
| dc.type | text |