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HaikuS2S: A Cascaded System For Responding In Verse

arXiv · AI, language, vision and robotics · article · Sep 20, 2026 · UTC

Expressive speech synthesis has advanced through prosody modeling, yet generating structured poetic speech, such as haiku, remains challenging. Prior work on prosody transfer improves expressiveness, and fine-tuned poetry TTS (text-to-speech) systems capture verse intonation. However, these models do not model haiku's 5-7-5 syllable structure or line-ending pauses. We present a cascaded system, HaikuS2S, combining ASR (automatic speech recognition), LLM (large language model)-generated haiku, and TTS fine-tuning on both prose and custom haiku datasets. Our evaluation focuses on emotion similar

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First collected: 2026-09-23T09:51:33.063Z. This is not the publication date.