🐢 Tortoise¶
Tortoise is a very expressive TTS system with impressive voice cloning capabilities. It is based on an GPT like autogressive acoustic model that converts input text to discritized acoustic tokens, a diffusion model that converts these tokens to melspectrogram frames and a Univnet vocoder to convert the spectrograms to the final audio signal. The important downside is that Tortoise is very slow compared to the parallel TTS models like VITS.
Big thanks to 👑@manmay-nakhashi who helped us implement Tortoise in 🐸TTS.
Example use¶
See also
from TTS.tts.configs.tortoise_config import TortoiseConfig
from TTS.tts.models.tortoise import Tortoise
config = TortoiseConfig()
model = Tortoise.init_from_config(config)
model.load_checkpoint(config, checkpoint_dir="paths/to/models_dir/", eval=True)
model.to("cuda")
# Random speaker
output_dict = model.synthesize(text)
# Cloning a speaker
output_dict = model.synthesize(text, speaker_wav="path/to/speaker.wav")
Using 🐸TTS API:
from TTS.api import TTS
tts = TTS("tts_models/en/multi-dataset/tortoise-v2").to("cuda")
# Clone voice and cache it with the custom ID `lj`
# with custom inference settings overriding defaults.
tts.tts_to_file(text="Hello, my name is Manmay , how are you?",
file_path="output.wav",
speaker_wav=["tests/data/ljspeech/wavs/LJ001-0001.wav"],
speaker="lj",
num_autoregressive_samples=1,
diffusion_iterations=10)
# Using presets with the same voice after it is cached.
tts.tts_to_file(text="Hello, my name is Manmay , how are you?",
file_path="output.wav",
speaker="lj",
preset="ultra_fast")
# Random voice generation
tts.tts_to_file(text="Hello, my name is Manmay , how are you?",
file_path="output.wav")
Using 🐸TTS Command line:
# Cloning the `lj` voice and cache it under that ID for later reuse without reference audio.
tts --model_name tts_models/en/multi-dataset/tortoise-v2 \
--text "This is an example." \
--out_path "output.wav" \
--speaker_wav tests/data/ljspeech/wavs/*.wav \
--speaker_idx "lj"
# Random voice generation
tts --model_name tts_models/en/multi-dataset/tortoise-v2 \
--text "This is an example." \
--out_path "output.wav"
Important resources & papers¶
Original Repo: https://github.com/neonbjb/tortoise-tts
Faster implementation: https://github.com/152334H/tortoise-tts-fast
Univnet: https://arxiv.org/abs/2106.07889
Latent Diffusion:https://arxiv.org/abs/2112.10752
DALL-E: https://arxiv.org/abs/2102.12092