Paper Info
Title
Named entities in judicial transcriptions: extended conditional random fields
Abstract
The progressive deployment of ICT technologies in the courtroom is leading to the development of integrated multimedia folders where the entire trial contents (documents, audio and video recordings) are available for online consultation via web-based platforms. The current amount of unstructured textual data available into the judicial domain, especially related to hearing transcriptions, highlights therefore the need to automatically extract structured data from the unstructured ones for improving the efficiency of consultation processes. In this paper we address the problem of extracting structured information from the transcriptions generated automatically using an ASR (Automatic Speech Recognition) system, by integrating Conditional Random Fields with available background information. The computational experiments show promising results in structuring ASR outputs, enabling a robust and efficient document consultation.
Year
DOI
Venue
2013
10.1007/978-3-642-37247-6_26
CICLing
Keywords
Field
DocType
extended conditional random field,consultation process,judicial transcription,unstructured textual data,automatic speech recognition,efficient document consultation,available background information,asr output,ict technology,conditional random fields,structured information,online consultation
Conditional random field,Transcription (linguistics),Software deployment,Computer science,Word error rate,Artificial intelligence,Natural language processing,Information and Communications Technology,Structuring,Named-entity recognition,Data model
Conference
Citations 
PageRank 
References 
3
0.42
8
Authors
2
Name
Order
Citations
PageRank
Elisabetta Fersini114020.70
Enza Messina221423.18