Parallel Corpora in Mboshi (Bantu C25, Congo-Brazzaville)

This article presents multimodal and parallel data collections in Mboshi, as part of the French-German BULB project. It aims at supporting documentation and providing digital resources for less resourced languages with the help of speech and language-based technology. The data collection specifications thus have to meet both field linguists' and computer scientists' requirements, which are large corpora for the latter and linguistically dense data for the former. Beyond speech, the collection comprises pictures and videos documenting social practices, agriculture, wildlife and plants. Visual supports aimed at encouraging people to comment on objects which are meaningful in their daily lives. Speech recordings are composed of the original speech in Mboshi, a respoken version and a translated version to French. These three speech streams remain time-aligned thanks to LIG-AIKUMA, which adds new features to a previous AIKUMA application. The speech corpus includes read material (5k sentences, Bible), verb conjugations and a large part of spontaneous speech (conversations, picture descriptions) resulting in over 50 hours of Mboshi speech, of which 20 hours are already respoken and orally translated to French. These parallel oral data are intended for linguistic documentation (tonology, phonology...) and automatic processing (corpus annotation, alignment between Mboshi speech and French translations).

[1]  Guy Noël Kouarata Variations de formes dans la langue Mbochi (Bantu C25) , 2014 .

[2]  Martine Adda-Decker,et al.  Lig-Aikuma: A Mobile App to Collect Parallel Speech for Under-Resourced Language Studies , 2016, INTERSPEECH.

[3]  Sebastian Stüker,et al.  Innovative technologies for under-resourced language documentation: The BULB Project , 2016 .

[4]  Lori Lamel,et al.  Developing an Embosi (Bantu C25) Speech Variant Dictionary to Model Vowel Elision and Morpheme Deletion , 2017, INTERSPEECH.

[5]  Laura J. Downing,et al.  How intonations interact with tones in Embosi (Bantu C25), a two-tone language without downdrift , 2016 .

[6]  Sebastian Stüker,et al.  A Very Low Resource Language Speech Corpus for Computational Language Documentation Experiments , 2017, LREC.

[7]  Alexandre Allauzen,et al.  Preliminary Experiments on Unsupervised Word Discovery in Mboshi , 2016, INTERSPEECH.

[8]  F. François Enquête et description des langues à tradition orale , 1973 .

[9]  Steven Bird,et al.  Aikuma: A Mobile App for Collaborative Language Documentation , 2014 .

[10]  Jong Kyoung Kim,et al.  Speech recognition , 1983, 1983 IEEE International Solid-State Circuits Conference. Digest of Technical Papers.

[11]  Jean-Luc Gauvain,et al.  Large Vocabulary Speech Recognition Based on Statistical Methods , 2003 .

[12]  Wayne H. Ward,et al.  Speech recognition , 1997 .

[13]  Lori Lamel,et al.  Dropping of the Class-Prefix Consonant, Vowel Elision and Automatic Phonological Mining in Embosi (Bantu C 25) , 2015 .

[14]  Sebastian Stüker,et al.  Breaking the Unwritten Language Barrier: The BULB Project , 2016, SLTU.

[15]  A G N,et al.  Bibliographical References , 1965 .

[16]  Georges Martial Embanga Aborobongui Processus segmentaux et tonals en Mbondzi - (variété de la langue embosi C25) - , 2013 .