Papers by Anna Katanova

2 papers
XTREME-UP: A User-Centric Scarce-Data Benchmark for Under-Represented Languages (2023.findings-emnlp)

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Challenge: Existing datasets are often informed by established research directions in the NLP community.
Approach: They propose a benchmark to evaluate the capabilities of language models across 88 under-represented languages over 9 key user-centric technologies including ASR, OCR, MT, and information access tasks.
Outcome: The proposed benchmark evaluates the capabilities of language models across 88 under-represented languages over 9 key user-centric technologies including ASR, OCR, MT, and information access tasks.
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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Challenge: We present free high quality multi-speaker speech corpora for Gujarati, Kannada, Malayalam, Marathi, Tamil and Telugu . the datasets are primarily intended for use in text-to-speech applications, such as constructing multilingual voices or language adaptation.
Approach: They present a free high quality multi-speaker speech corpora for Gujarati, Kannada, Malayalam, Marathi, Tamil and Telugu . they use it to build a multilingual text-to-speech model that can be scaled to other languages of interest.
Outcome: The proposed model produces good quality voices with MOS > 3.6 for all the languages tested.

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