IRINTS: Irisa News Topic Segmenter

Description:

IRINTS (Irisa News Topic Segmenter) was designed for topic segmentation of broadcast news transcripts.

• The distribution includes a front-end script, ‘irints’, which is merely a wrapper to the main ‘topic-segmenter’ program included herein (topic-segmenter, release 1.1 [1] ).
• The topic-segmenter program is a software dedicated to topic segmentation of texts and (automatic) transcripts, mostly based on lexical cohesion, implementing (and extending) a method described in [2].
• A bunch of goodies, such as the use of alternate knowledge sources, were added. For more details (and assuming you can read the French language), please refer to [3].

As shown on figure 1 below, input to IRINTS is an automatic transcript (in Vecsys’s VOX format or IRISA’s SSD format). The output is an XML file in SSD format specifying topic segments.

[1] http://gforge.inria.fr/projects/topic-segmenter/
[2] Masao Utiyama and Hitoshi Isahara, «A Statistical Model for Domain-Independent Text Segmentation», ACL, 491–498, 2001
[3] S. Huet, G. Gravier and P. Sébillot, «Un modèle multisources pour la segmentation en sujets de journaux radiophoniques», in Proc. Traitement Automatique des Langues Naturelles, 2008.

IRINTS was developed at Irisa in Rennes by the Texmex and Metiss teams.
The IRINTS authors are: Guillaume Gravier, Camille Guinaudeau