| Challenge: | Existing research and development areas in speech recognition are focused on the language of speakers. |
| Approach: | They propose to use a bilingual (English-Farsi) speech corpus to validate and explore speaker verification systems. |
| Outcome: | The proposed corpus can be used in a variety of language dependent and independent applications. |
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| Challenge: | a corpus of multilingual Arabic-English speech is presented in a new paper . a major bottleneck is the lack of data needed for training NLP models . |
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CVSS Corpus and Massively Multilingual Speech-to-Speech Translation (2022.lrec-1)
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Omid Ghahroodi, Arshia Hemmat, Marzia Nouri, Seyed Mohammad Hadi Hosseini, Doratossadat Dastgheib, Mohammad Vali Sanian, Alireza Sahebi, Reihaneh Zohrabi, Mohammad Hossein Rohban, Ehsaneddin Asgari, Mahdieh Soleymani Baghshah
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A Survey of Multilingual Models for Automatic Speech Recognition (2022.lrec-1)
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| Challenge: | Automatic Speech Recognition (ASR) systems have achieved human-like performance for a few languages, but the majority of the world’s languages do not have usable systems due to the lack of large speech datasets to train these models. |
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Open-source Multi-speaker Speech Corpora for Building Gujarati, Kannada, Malayalam, Marathi, Tamil and Telugu Speech Synthesis Systems (2020.lrec-1)
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Fei He, Shan-Hui Cathy Chu, Oddur Kjartansson, Clara Rivera, Anna Katanova, Alexander Gutkin, Isin Demirsahin, Cibu Johny, Martin Jansche, Supheakmungkol Sarin, Knot Pipatsrisawat
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