Domain Adaptation with Clustered Language Models
<|reference_start|>Domain Adaptation with Clustered Language Models: 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.<|reference_end|>
@article{ueberla1997domain,
    title={Domain Adaptation with Clustered Language Models},
    author={Joerg P. Ueberla (Forum Technology - DRA Malvern)},
    journal={arXiv preprint arXiv:cmp-lg/9703001},
    year={1997},
    archivePrefix={arXiv},
    eprint={cmp-lg/9703001},
    primaryClass={cmp-lg cs.CL}
}