Papers with Generative Spoken Language Model

1 papers
Generative Spoken Language Model based on continuous word-sized audio tokens (2023.emnlp-main)

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Challenge: Text-based language models outperform character-based models, but speech inputs are 20ms or 40ms-long discrete units.
Approach: They propose a generative language model based on word-size continuous audio tokens . they replace lookup table for lexical types with a Lexical Embedding function .
Outcome: The proposed model is five times more memory efficient than discrete unit GSLMs and is phonetically and semantically interpretable.

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