What is MegaTTS 3
MegaTTS 3 is a zero-shottext-to-speechsynthesis system jointly launched by ByteDance and Zhejiang University. It adopts a lightweight diffusion model with only 0.45B parameters and can efficiently generate high-quality speech. The system decomposes speech into attributes such as content, timbre, and prosody for separate modeling, supports Chinese, English, and mixed Chinese-English speech synthesis, and has ultra-high sound qualityvoice cloningcapabilities, and can imitate the target voice with just a few seconds of audio samples. It supports controllability functions such as accent intensity control. MegaTTS 3 can be applied to multiple scenarios such as speech synthesis, speech editing, and cross-lingual speech synthesis.
Main Features of MegaTTS 3
- Zero-Shot Synthesis: It does not require specific speech data from the target speaker and can generate their voice with only a small amount of prompting, enabling rapid voice cloning.
- Multilingual Support: It supports Chinese, English, and mixed Chinese-English speech synthesis, meeting the needs of different language scenarios.
- High-Quality Output: The generated speech is natural and fluent, with clear sound quality, and is highly similar to the target speaker.
- Timbre Control: The timbre of the generated speech can be adjusted to be closer to the target speaker or to add specific timbre effects.
- Prosody Adjustment: It supports control over the prosody of speech, such as speaking rate and intonation, making the speech more expressive.
- Accent Intensity Control: Through parameter adjustment, it can generate speech with different accent intensities, simulating a variety of language styles.
- Fast Cloning: It only needs a few seconds of audio samples from the target speaker to quickly generate their voice, enabling efficient voice cloning.
Technical Principles of MegaTTS 3
- Lightweight Diffusion Model: MegaTTS 3 adopts a lightweight diffusion model (TTS Diffusion Transformer) with only 0.45B parameters, which can generate high-quality speech while ensuring efficiency. The diffusion model generates the target speech by gradually adding and removing noise, with the core including a forward process (adding noise) and a reverse process (denoising); the reverse process is used to generate data samples.
- Speech Decomposition and Modeling: MegaTTS 3 decomposes speech into different attributes such as content, timbre, prosody, and phase, and designs suitable modules for modeling each attribute:
- Timbre Modeling: Global vectors are used to model timbre because timbre is a global attribute that changes slowly over time.
- Prosody Modeling: A latent code language model is used to fit the distribution of prosody because prosody changes rapidly within a sentence, and the language model can capture local and long-range dependencies.
- Content Modeling: A VQGAN-based acoustic model is used to generate spectrograms.
- Phase Modeling: The phase is appropriately constructed by a GAN-based vocoder, and there is no need for a language model to model the phase.
- Data and Training: MegaTTS 3 is trained on a large-scale multi-domain dataset containing 20K hours of speech data. This enables the model to perform excellently on zero-shot speech synthesis, speech editing, and cross-lingual speech synthesis tasks.
- Sparse Alignment Algorithm: MegaTTS 3 introduces a sparse alignment algorithm, providing sparse alignment boundaries to guide the latent Diffusion Transformer (DiT), reducing alignment difficulty without shrinking the search space and achieving high naturalness.
MegaTTS 3 project address
- Github repository：https://github.com/bytedance/MegaTTS3
- HuggingFace model repository：https://huggingface.co/ByteDance/MegaTTS3
MegaTTS 3 application scenarios
- Academic research: Researchers can use it to test speech synthesis technology and analyze the effects of latents.
- Educational assistance: Convert textbooks into speech and generate audiobooks to enhance the learning experience.
- Content production: Generate narration for videos or podcasts, saving the cost of manual recording.
- Voice interaction: Developers can integrate it into devices to enable Chinese-English voice conversations.