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All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year Sort by creator [A → Z]' creator [Z → A]' publishing year ↑ (asc)' publishing year ↓ (desc)' title [A → Z]' title [Z → A]' Simple Search Hits 1 – 3 of 3 1 A Very Low Resource Language Speech Corpus for Computational Language Documentation Experiments Godard, P.; Adda, G; Adda-Decker, Martine... In: Language Resources and Evaluation Conference (LREC) ; https://hal.archives-ouvertes.fr/hal-01807093 ; Language Resources and Evaluation Conference (LREC), Nicoletta Calzolari (Conference chair) and Khalid Choukri and Christopher Cieri and Thierry Declerck and Sara Goggi and Koiti Hasida and Hitoshi Isahara and Bente Maegaard and Joseph Mariani and Hélène Mazo and Asuncion Moreno and Jan Odijk and Stelios Pi, May 2018, Miyazaki, Japan (2018) BASE Show details 2 Unsupervised word segmentation from speech with attention Godard, P.; Boito, M.Z.; Ondel, L.. - : ISCA, 2018 BASE Show details 3 A Very Low Resource Language Speech Corpus for Computational Language Documentation Experiments ... Godard, P.; Adda, G.; Adda-Decker, M.; Benjumea, J.; Besacier, L.; Cooper-Leavitt, J.; Kouarata, G-N.; Lamel, L.; Maynard, H.; Mueller, M.; Rialland, A.; Stueker, S.; Yvon, F.; Zanon-Boito, M.. - : arXiv, 2017 Abstract: Most speech and language technologies are trained with massive amounts of speech and text information. However, most of the world languages do not have such resources or stable orthography. Systems constructed under these almost zero resource conditions are not only promising for speech technology but also for computational language documentation. The goal of computational language documentation is to help field linguists to (semi-)automatically analyze and annotate audio recordings of endangered and unwritten languages. Example tasks are automatic phoneme discovery or lexicon discovery from the speech signal. This paper presents a speech corpus collected during a realistic language documentation process. It is made up of 5k speech utterances in Mboshi (Bantu C25) aligned to French text translations. Speech transcriptions are also made available: they correspond to a non-standard graphemic form close to the language phonology. We present how the data was collected, cleaned and processed and we illustrate its ... : accepted to LREC 2018 ... Keyword: Computation and Language cs.CL; FOS Computer and information sciences URL: https://dx.doi.org/10.48550/arxiv.1710.03501 https://arxiv.org/abs/1710.03501 BASE Hide details

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