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Articles

ChatQA 2: Bridging the Gap to Proprietary LLMs in Long Context and RAG Capabilities

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By Wei Ping, Xianchao Wu, Zihan Liu, Mohammad Shoeybi
| arxiv.org
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Improving Japanese Language ASR by Combining Convolutions with Attention Mechanisms

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By Somshubra Majumdar, Xianchao Wu
| NVIDIA
Automatic speech recognition (ASR) research generally focuses on high-resource languages such as English, which is supported by hundreds of thousands of hours of speech. Recent literature has renewed focus on more complex languages, such as Japanese. Like other Asian languages, Japanese has a vast base character set (upwards of 3,000 unique characters are used in common vernacular), and poses unique challenges, such as multiple word order.
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