Abstract
The extraction of flat concepts out of a given word sequence is usually one of the first steps in building a spoken language understanding (SLU) or dialogue system. This paper explores five different modelling approaches for this task and presents results on a French state-of-the-art corpus, MEDIA. Additionally, two log-linear modelling approaches could be further improved by adding morphologic knowledge. This paper goes beyond what has been reported in the literature. We applied the models on the same training and testing data and used the NIST scoring toolkit to evaluate the experimental results to ensure identical conditions for each of the experiments and the comparability of the results. Using a model based on conditional random fields, we achieve a concept error rate of 11.8% on the MEDIA evaluation corpus.- Anthology ID:
- L08-1495
- Volume:
- Proceedings of the Sixth International Conference on Language Resources and Evaluation (LREC'08)
- Month:
- May
- Year:
- 2008
- Address:
- Marrakech, Morocco
- Editors:
- Nicoletta Calzolari, Khalid Choukri, Bente Maegaard, Joseph Mariani, Jan Odijk, Stelios Piperidis, Daniel Tapias
- Venue:
- LREC
- SIG:
- Publisher:
- European Language Resources Association (ELRA)
- Note:
- Pages:
- Language:
- URL:
- http://www.lrec-conf.org/proceedings/lrec2008/pdf/749_paper.pdf
- DOI:
- Cite (ACL):
- Stefan Hahn, Patrick Lehnen, Christian Raymond, and Hermann Ney. 2008. A Comparison of Various Methods for Concept Tagging for Spoken Language Understanding. In Proceedings of the Sixth International Conference on Language Resources and Evaluation (LREC'08), Marrakech, Morocco. European Language Resources Association (ELRA).
- Cite (Informal):
- A Comparison of Various Methods for Concept Tagging for Spoken Language Understanding (Hahn et al., LREC 2008)
- PDF:
- http://www.lrec-conf.org/proceedings/lrec2008/pdf/749_paper.pdf