Spectron

End-to-end spectrogram modeling: Processes spectrograms directly without an intermediate speech-recognition or tokenization step, preserving paralinguistic information.

High-quality spoken output: Fine-tuned to generate high-quality, accurate spoken language while preserving speaker and prosody characteristics.

Speaker preservation: Outperforms prior spoken-language models on speaker preservation - a known weakness of tokenizer-based approaches.

Semantic coherence: Also improves semantic coherence of generated speech, addressing the common drift problem in spectrogram-level generation.