Name
Title | ||
|---|---|---|
Etiqueter un corpus oral par apprentissage automatique à l'aide de connaissances linguistiques |
Abstract | ||
|---|---|---|
Thanks to the Eslo1 ("Enqu\^ete sociolinguistique d'Orl\'eans", i.e.
"Sociolinguistic Inquiery of Orl\'eans") campain, a large oral corpus has been
gathered and transcribed in a textual format. The purpose of the work presented
here is to associate a morpho-syntactic label to each unit of this corpus. To
this aim, we have first studied the specificities of the necessary labels, and
their various possible levels of description. This study has led to a new
original hierarchical structuration of labels. Then, considering that our new
set of labels was different from the one used in every available software, and
that these softwares usually do not fit for oral data, we have built a new
labeling tool by a Machine Learning approach, from data labeled by Cordial and
corrected by hand. We have applied linear CRF (Conditional Random Fields)
trying to take the best possible advantage of the linguistic knowledge that was
used to define the set of labels. We obtain an accuracy between 85 and 90%,
depending of the parameters used. |
Year | Venue | DocType |
|---|---|---|
2010 | Computing Research Repository | Journal |
Volume | Citations | PageRank |
abs/1003.5 | 0 | 0.34 |
References | Authors | |
3 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Iris Eshkol | 1 | 2 | 1.43 |
| isabelle tellier | 2 | 84 | 20.31 |
| Taalab Samer | 3 | 0 | 0.34 |
| Sylvie Billot | 4 | 100 | 15.69 |