| Challenge: | Epitran is a multilingual, multi-back-end system for grapheme-to-phoneme transduction . it supports 61 languages and is open source under an MIT license . |
| Approach: | Epitran is a multilingual back-end system for grapheme-to-phoneme transduction . it takes word tokens in the orthography of a language and outputs a phonemic representation . Epitran's efficacy has been demonstrated in multiple research projects . |
| Outcome: | Epitran is a multilingual, multi-backend system for grapheme-to-phoneme transduction . it supports 61 languages and is open source under MIT license . |
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| Challenge: | Grapheme-to-phoneme conversion (g2p) is a task of predicting the pronunciation of words from their orthographic representation. |
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| Challenge: | Existing text-to-speech systems struggle to produce natural speech from grapheme sequences . Grapheme-to phoneme conversion (G2P) systems face limitations when dealing with Persian texts due to the complexity of Persian transcription. |
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Ayyoob ImaniGooghari, Peiqin Lin, Amir Hossein Kargaran, Silvia Severini, Masoud Jalili Sabet, Nora Kassner, Chunlan Ma, Helmut Schmid, André Martins, François Yvon, Hinrich Schütze
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| Challenge: | Existing work focuses on low-resource and endangered languages with limited training sets. |
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Massively Multilingual Adversarial Speech Recognition (N19-1)
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| Challenge: | Prior work in multilingual and cross-lingual speech recognition has been limited to a subset of the world's most-spoken languages. |
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