Papers with cascades

2 papers
Phone Features Improve Speech Translation (2020.acl-main)

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Challenge: End-to-end models for speech translation more tightly couple speech recognition (ASR) and machine translation (MT) compared to cascades, but performance gap remains in low-resource conditions .
Approach: They propose two methods to incorporate phone features into current neural speech translation models.
Outcome: The proposed models outperform existing models and cascades by up to 9 BLEU on low-resource conditions.
AudioChatLlama: Towards General-Purpose Speech Abilities for LLMs (2024.naacl-long)

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Challenge: a new model for speech processing and reasoning uses curated data instead of text.
Approach: They extend the instruction-tuned Llama-2 model with end-to-end speech processing and reasoning abilities without using any carefully curated paired data.
Outcome: The proposed model outperforms or outperfects existing models on synthesized and recorded speech QA tests.

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