TEDxTN: A Three-way Speech Translation Corpus for Code-Switched Tunisian Arabic - English

TL;DR

TEDxTN is the first publicly available Tunisian Arabic to English speech translation dataset, enabling research on code-switching and dialect-specific NLP tasks with 25 hours of annotated speech from diverse speakers.

Contribution

This paper introduces TEDxTN, the first open-source Tunisian Arabic-English speech translation corpus with code-switching, including annotation guidelines and baseline system results.

Findings

Achieved baseline speech recognition and translation performance.

Provided a diverse dataset covering multiple Tunisian regions.

Enabled future research in Tunisian dialect NLP.

Abstract

In this paper, we introduce TEDxTN, the first publicly available Tunisian Arabic to English speech translation dataset. This work is in line with the ongoing effort to mitigate the data scarcity obstacle for a number of Arabic dialects. We collected, segmented, transcribed and translated 108 TEDx talks following our internally developed annotations guidelines. The collected talks represent 25 hours of speech with code-switching that cover speakers with various accents from over 11 different regions of Tunisia. We make the annotation guidelines and corpus publicly available. This will enable the extension of TEDxTN to new talks as they become available. We also report results for strong baseline systems of Speech Recognition and Speech Translation using multiple pre-trained and fine-tuned end-to-end models. This corpus is the first open source and publicly available speech translation corpus of Code-Switching Tunisian dialect. We believe that this is a valuable resource that can motivate and facilitate further research on the natural language processing of Tunisian Dialect.