MOSS-TTS Technical Report
📰 ArXiv cs.AI
MOSS-TTS is a speech generation foundation model built on discrete audio tokens and autoregressive modeling
Action Steps
- Utilize MOSS-Audio-Tokenizer for causal Transformer tokenization of audio
- Apply autoregressive modeling for speech generation
- Leverage large-scale pretraining for improved performance
- Explore applications of MOSS-TTS in speech synthesis and audio processing
Who Needs to Know This
AI engineers and researchers on a team can benefit from MOSS-TTS as it provides a scalable recipe for speech generation, while product managers can explore its applications in various products
Key Insight
💡 MOSS-TTS provides a scalable recipe for speech generation using discrete audio tokens and autoregressive modeling
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💡 MOSS-TTS: a scalable speech generation model using discrete audio tokens & autoregressive modeling
Key Takeaways
MOSS-TTS is a speech generation foundation model built on discrete audio tokens and autoregressive modeling
Full Article
Title: MOSS-TTS Technical Report
Abstract:
arXiv:2603.18090v2 Announce Type: replace-cross Abstract: This technical report presents MOSS-TTS, a speech generation foundation model built on a scalable recipe: discrete audio tokens, autoregressive modeling, and large-scale pretraining. Built on MOSS-Audio-Tokenizer, a causal Transformer tokenizer that compresses 24 kHz audio to 12.5 fps with variable-bitrate RVQ and unified semantic-acoustic representations, we release two complementary generators: MOSS-TTS, which emphasizes structural simp
Abstract:
arXiv:2603.18090v2 Announce Type: replace-cross Abstract: This technical report presents MOSS-TTS, a speech generation foundation model built on a scalable recipe: discrete audio tokens, autoregressive modeling, and large-scale pretraining. Built on MOSS-Audio-Tokenizer, a causal Transformer tokenizer that compresses 24 kHz audio to 12.5 fps with variable-bitrate RVQ and unified semantic-acoustic representations, we release two complementary generators: MOSS-TTS, which emphasizes structural simp
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