Publication Details
Morphological random forests for language modeling of inflectional languages
Glembek Ondřej, Ing., Ph.D. (DCGM FIT BUT)
Burget Lukáš, doc. Ing., Ph.D. (DCGM FIT BUT)
Černocký Jan, prof. Dr. Ing. (DCGM FIT BUT)
speech recognition, language modeling
The paper is on morphological random forests for language modeling of inflectional languages
In this paper, we are concerned with using decision trees (DT) and random forests (RF) in language modeling for Czech LVCSR. We show that the RF approach can be successfully implemented for language modeling of an inflectional language. Performance of word-based and morphological DTs and RFs was evaluated on lecture recognition task. We show that while DTs perform worse than conventional trigram language models (LM), RFs of both kind outperform the latter. WER (up to 3.4% relative) and perplexity (10%) reduction over the trigram model can be gained with morphological RFs. Further improvement is obtained after interpolation of DT and RF LMs with the trigram one (up to 15.6% perplexity and 4.8% WER relative reduction). In this paper we also investigate distribution of morphological feature types chosen for splitting data at different levels of DTs.
@INPROCEEDINGS{FITPUB8844, author = "Ilya Oparin and Ond\v{r}ej Glembek and Luk\'{a}\v{s} Burget and Jan \v{C}ernock\'{y}", title = "Morphological random forests for language modeling of inflectional languages", pages = 4, booktitle = "Proc. 2008 IEEE Workshop on Spoken Language Technology", year = 2008, location = "Goa, IN", publisher = "IEEE Signal Processing Society", ISBN = "978-1-4244-3472-5", language = "english", url = "https://www.fit.vut.cz/research/publication/8844" }