Yes, we can use Coqui with RVC!
Coqui is a text-to-speech framework (vocoder and encoder), but cloning your own voice takes decades and offers no guarantee of better results. That's why we use RVC (Retrieval-Based Voice Conversion), which works only for speech-to-speech. You can train the model with just 2-3 minutes of dataset as it uses Hubert (a pre-trained model to fine-tune quickly and provide better results).
How to use Coqui + RVC api?
https://github.com/skshadan/TTS-RVC-API.git
python -m venv .venv
. .venv/bin/activate
pip install -r requirements.txt
pip install TTS
python -m uvicorn app.main:app
Now update config.toml
with relative paths
config model_dir
path or set a speaker_name
in the request body
Where the RVC v2 model is mounted on the container at:
/
└── models
└── speaker1
├── speaker1.pth
└── speaker1.index
Now Run this
python -m uvicorn app.main:app
http://localhost:8000/generate
emotions : happy,sad,angry,dull
speed = 1.0 - 2.0
{
"speaker_name": "speaker3",
"input_text": "Hey there! Welcome to the world",
"emotion": "Surprise",
"speed": 1.0
}
import requests
import json
import time
url = "http://127.0.0.1:8000/generate"
payload = json.dumps({
"speaker_name": "speaker3",
"input_text": "Are you mad? The way you've betrayed me is beyond comprehension, a slap in the face that's left me boiling with an anger so intense it's as if you've thrown gasoline on a fire, utterly destroying any trust that was left.",
"emotion": "Dull",
"speed": 1.0
})
headers = {
'Content-Type': 'application/json'
}
start_time = time.time() # Start the timer
response = requests.request("POST", url, headers=headers, data=payload)
end_time = time.time() # Stop the timer
if response.status_code == 200:
audio_content = response.content
# Save the audio to a file
with open("generated_audio.wav", "wb") as audio_file:
audio_file.write(audio_content)
print("Audio saved successfully.")
print("Time taken:", end_time - start_time, "seconds")
else:
print("Error:", response.text)
If you have any feedback, issues please reach out to shadankhantech@gmail.com