How to Use MeloTTS for High-Quality Text-to-Speech

Mar 3, 2024 | Educational

MeloTTS is a high-quality multi-lingual text-to-speech (TTS) library developed by MyShell.ai. With support for several languages and a host of features, MeloTTS enables developers and enthusiasts alike to convert text into natural-sounding speech. In this guide, we’ll walk you through how to get started with MeloTTS, use it without installation, and troubleshoot any issues you might encounter along the way.

Supported Languages

MeloTTS supports various English accents and languages:

Using MeloTTS Without Installation

If you want to try out MeloTTS without going through the installation process, you can use an unofficial live demo hosted on Hugging Face Spaces. This option is perfect for testing the capabilities of the library.

Install and Use MeloTTS Locally

To use MeloTTS locally, you need to follow the installation steps detailed here. Once you have it installed, you can start using it with the following Python code snippet:

python
from melo.api import TTS

# Speed is adjustable
speed = 1.0
device = cpu # or cuda:0
text = "La lueur dorée du soleil caresse les vagues, peignant le ciel d'une palette éblouissante."
model = TTS(language=FR, device=device)
speaker_ids = model.hps.data.spk2id
output_path = 'fr.wav'
model.tts_to_file(text, speaker_ids[FR], output_path, speed=speed)

Explaining the Code with an Analogy

Think of MeloTTS as a professional chef who needs to create a delightful dish (speech) from a set of ingredients (text). The ingredients have to be properly prepared before coming together to create a meal.

Ingredients (text): Just like a good chef needs quality ingredients, the text you input is crucial for the final spoken output.
Cooking Speed (speed variable): The chef can adjust how quickly they cook. Similarly, you can change the speed in which the text is spoken with the speed variable in the code.
The Cooking Device (device): The type of stove or oven—a CPU is like a regular oven while a CUDA device is a high-powered professional stove designed to cook multiple dishes at once (run the conversion faster).
Serving Plate (output_path): Finally, the chef serves the meal on a plate. In this case, the output path tells MeloTTS where to save its delicious speech creation.

Troubleshooting

If you encounter any issues while using MeloTTS, here are some troubleshooting ideas:

Ensure you have installed all dependencies properly. Check the installation instructions again.
Verify your Python environment is correctly set up. Sometimes, the version of Python can affect compatibility.
If you experience slow performance, consider using a CUDA device if available.
For any bugs or specific errors, consult the GitHub repository’s issues page or documentation for solutions.

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Conclusion

At fxis.ai, we believe that such advancements are crucial for the future of AI, as they enable more comprehensive and effective solutions. Our team is continually exploring new methodologies to push the envelope in artificial intelligence, ensuring that our clients benefit from the latest technological innovations.

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