However, the system's reliance on a large, high-quality speech dataset for training could limit its applicability in real-world applications where such datasets may not be readily available. The paper also does not explore the system's robustness to noisy or low-quality input data. Despite these limitations, NaturalSpeech 3 represents a significant advancement in zero-shot speech synthesis.
Key takeaways:
- NaturalSpeech 3 is a new zero-shot speech synthesis system that uses factorized codec and diffusion models to generate high-quality speech without needing any target speaker data.
- The system breaks down the speech signal into two separate components: one that captures the linguistic content and another that captures the speaker's unique voice characteristics, allowing it to generate new speech in any voice.
- NaturalSpeech 3 outperforms previous zero-shot and few-shot speech synthesis approaches, and could have applications in areas like voice-based assistants, audio-book narration, and dubbing for films and TV shows.
- Despite its advancements, the system's reliance on large, high-quality speech datasets for training and unexplored robustness to noisy or low-quality input data are potential limitations.