fastspeech2-en-ljspeech
Maintainer: facebook
245
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| Property | Value |
|---|---|
| Run this model | Run on HuggingFace |
| API spec | View on HuggingFace |
| Github link | No Github link provided |
| Paper link | No paper link provided |
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Model overview
The fastspeech2-en-ljspeech model is a text-to-speech (TTS) model from Facebook's fairseq S^2 project. It is a FastSpeech 2 model trained on the LJSpeech dataset, which contains a single-speaker female voice in English.
Model inputs and outputs
Inputs
- Text: The model takes in text as input, which is then converted to speech.
Outputs
- Audio: The model outputs a waveform representing the synthesized speech.
Capabilities
The fastspeech2-en-ljspeech model can be used to convert text to high-quality, natural-sounding speech in English. It is a non-autoregressive model, which means it can generate the entire audio output in a single pass, resulting in faster inference compared to autoregressive TTS models.
What can I use it for?
The fastspeech2-en-ljspeech model can be used in a variety of applications that require text-to-speech functionality, such as audiobook generation, voice assistants, and text-based games or applications. The fast inference speed of the model makes it well-suited for real-time or streaming applications.
Things to try
Developers can experiment with the fastspeech2-en-ljspeech model by integrating it into their own applications or projects. For example, they could use the model to generate audio versions of written content, or to add speech capabilities to conversational interfaces. The model's single-speaker female voice could also be used to create personalized TTS experiences.
This summary was produced with help from an AI and may contain inaccuracies - check out the links to read the original source documents!
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