PlanRAG-Audio introduces planning-based retrieval-augmented generation to improve accuracy and stability of long-form audio understanding in LALMs by decoupling model input from raw audio duration.
HuBERT: Self-Supervised Speech Representation Learning by Masked Prediction of Hidden Units , year=
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Multilingual generative meta-learning for spoken word classification shows small gains over monolingual models, with unique data volume mattering more than the number of languages.
GeMCL achieves stable 1000-class few-shot spoken word classification with 5 shots per class, comparable to finetuned HuBERT but 2000x faster adaptation using less data and time.
citing papers explorer
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PlanRAG-Audio: Planning and Retrieval Augmented Generation for Long-form Audio Understanding
PlanRAG-Audio introduces planning-based retrieval-augmented generation to improve accuracy and stability of long-form audio understanding in LALMs by decoupling model input from raw audio duration.
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Does language matter for spoken word classification? A multilingual generative meta-learning approach
Multilingual generative meta-learning for spoken word classification shows small gains over monolingual models, with unique data volume mattering more than the number of languages.
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Scaling few-shot spoken word classification with generative meta-continual learning
GeMCL achieves stable 1000-class few-shot spoken word classification with 5 shots per class, comparable to finetuned HuBERT but 2000x faster adaptation using less data and time.