arXiv Machine Learning By Fritz Cremer, Jonathan Cremer

TontaubeV1: Streaming Text-to-Speech with Hierarchical Codec Modeling and Bounded Context

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TontaubeV1 is a streaming text‑to‑speech model that preserves natural prosody while running on a single consumer GPU. It encodes speech with a hierarchical DualCodec representation at 12.5 Hz, separating a semantic stream from successive acoustic refinements, and uses Qwen3‑derived transformers to predict the semantic stream, utterance duration, and acoustic refinements. The system supports up to one minute of reference audio for voice conditioning, streams with a 200 ms latency to first audio, and achieves real‑time factors of 0.08 (single input) and 0.02 (eight concurrent inputs).

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TontaubeV1: Streaming Text-to-Speech with Hierarchical Codec Modeling and Bounded Context

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