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Multilingual spoken dialogue systems still struggle with consistent performance across languages, even with high-resource languages, as shown by a new large-scale dataset.
Deploying language models in the Global South requires bridging the gap between multilingual NLP and edge computing, two fields that have largely evolved independently despite their shared goals.
