IndicContextEval is a new 56-hour multilingual benchmark and 7-level prompting framework for evaluating context utilization in AudioLLMs across 8 Indic languages.
Br-asr: Efficient and scalable bias retrieval framework for contextual biasing asr in speech llm,
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JSPG jointly combines semantic, pinyin, and glyph retrieval with an extended Smith-Waterman algorithm to dynamically filter keyword dictionaries and improve accuracy in Chinese contextual ASR.
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IndicContextEval: A Benchmark for Evaluating Context Utilisation in Audio Large Language Models Across 8 Indic Languages
IndicContextEval is a new 56-hour multilingual benchmark and 7-level prompting framework for evaluating context utilization in AudioLLMs across 8 Indic languages.
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JSPG: Dynamic Dictionary Filtering via Joint Semantic-Pinyin-Glyph Retrieval for Chinese Contextual ASR
JSPG jointly combines semantic, pinyin, and glyph retrieval with an extended Smith-Waterman algorithm to dynamically filter keyword dictionaries and improve accuracy in Chinese contextual ASR.