no code implementations • WS 2020 • Hafte Abera, sebsibe hailemariam
Therefore a Tigrinya large vocabulary continuous speech recognition system often has a large number of different units and a high out-of-vocabulary (OOV) rate if a word is used as a recognition unit of a language model (LM) and lexicon.
Automatic Speech Recognition Automatic Speech Recognition (ASR) +3
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
no code implementations • LREC 2020 • Solomon Teferra Abate, Martha Yifiru Tachbelie, Michael Melese, Hafte Abera, Tewodros Abebe, Wondwossen Mulugeta, Yaregal Assabie, Million Meshesha, Solomon Afnafu, Binyam Ephrem Seyoum
To assess usability of the corpora for (the purpose of) speech processing, we have developed ASR systems for each language.
Automatic Speech Recognition Automatic Speech Recognition (ASR) +1
no code implementations • WS 2019 • Hafte Abera, Sebsibe H/mariam
This work presents a speech recognition model for Tigrinya language . The Deep Neural Network is used to make the recognition model.
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.
no code implementations • COLING 2018 • Solomon Teferra Abate, Michael Melese, Martha Yifiru Tachbelie, Million Meshesha, Solomon Atinafu, Wondwossen Mulugeta, Yaregal Assabie, Hafte Abera, Binyam Ephrem, Tewodros Abebe, Wondimagegnhue Tsegaye, Amanuel Lemma, Tsegaye Andargie, Seifedin Shifaw
Based on the results we obtained, we are currently working towards handling the morphological complexities to improve the performance of statistical machine translation among the Ethiopian languages.
no code implementations • COLING 2018 • Hafte Abera, Sebsibe H/mariam
The authors provide also procedures that were used for the creation of Tigrinya speech recognition corpus which is the under-resourced language.
no code implementations • COLING 2018 • Solomon Teferra Abate, Michael Melese, Martha Yifiru Tachbelie, Million Meshesha, Solomon Atinafu, Wondwossen Mulugeta, Yaregal Assabie, Hafte Abera, Binyam Ephrem, Tewodros Abebe, Wondimagegnhue Tsegaye, 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.