ESLO: from transcription to speakers' personal information annotation

TL;DR

This paper describes the digitization, transcription, and multi-level annotation of a French oral corpus from 1968, focusing on recognizing and annotating speakers' personal information using cascade systems.

Contribution

It introduces a method for annotating speakers' personal information in oral corpora using cascaded recognition systems, with modifications for improved accuracy.

Findings

Achieved high precision and recall in recognizing named entities.

Successfully annotated personal information about speakers.

Demonstrated the feasibility of automated annotation in oral corpora.

Abstract

This paper presents the preliminary works to put online a French oral corpus and its transcription. This corpus is the Socio-Linguistic Survey in Orleans, realized in 1968. First, we numerized the corpus, then we handwritten transcribed it with the Transcriber software adding different tags about speakers, time, noise, etc. Each document (audio file and XML file of the transcription) was described by a set of metadata stored in an XML format to allow an easy consultation. Second, we added different levels of annotations, recognition of named entities and annotation of personal information about speakers. This two annotation tasks used the CasSys system of transducer cascades. We used and modified a first cascade to recognize named entities. Then we built a second cascade to annote the designating entities, i.e. information about the speaker. These second cascade parsed the named entity annotated corpus. The objective is to locate information about the speaker and, also, what kind of information can designate him/her. These two cascades was evaluated with precision and recall measures.