A Translation-Based Approach to Morphology Learning for Low Resource Languages

no code implementations • WS 2020 • Tewodros Gebreselassie, Amanuel Mersha, Michael Gasser

Specifically, we use a transfer-based approach to learn the morphology of the severely under-resourced language Gofa, starting with a neural morphological generator for the closely related language, Wolaytta.

Decoder Morphological Analysis +1

Large Vocabulary Read Speech Corpora for Four Ethiopian Languages: Amharic, Tigrigna, Oromo, and Wolaytta

no code implementations • WS 2020 • Solomon Teferra Abate, Martha Yifiru Tachbelie, Michael Melese, Hafte Abera, Tewodros Gebreselassie, Wondwossen Mulugeta, Yaregal Assabie, Million Meshesha Beyene, Solomon Atinafu, Binyam Ephrem Seyoum

To address this problem we have developed four medium-sized (longer than 22 hours each) speech corpora for four Ethiopian languages: Amharic, Tigrigna, Oromo, and Wolaytta.

Automatic Speech Recognition Automatic Speech Recognition (ASR) +1

English-Ethiopian Languages Statistical Machine Translation

no code implementations • WS 2019 • Solomon Teferra Abate, Michael Melese, Martha Yifiru Tachbelie, Million Meshesha, Solomon Atinafu, Wondwossen Mulugeta, Yaregal Assabie, Hafte Abera, Biniyam Ephrem, Tewodros Gebreselassie, Wondimagegnhue Tsegaye Tufa, Amanuel Lemma, Tsegaye Andargie, Seifedin Shifaw

In this paper, we describe an attempt towards the development of parallel corpora for English and Ethiopian Languages, such as Amharic, Tigrigna, Afan-Oromo, Wolaytta and Ge{'}ez.

Machine Translation Translation