tts-tacotron2-ljspeech
Maintainer: speechbrain
113
✅
| 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 tts-tacotron2-ljspeech model is a Text-to-Speech (TTS) model developed by SpeechBrain that uses the Tacotron2 architecture trained on the LJSpeech dataset. This model takes in text input and generates a spectrogram output, which can then be converted to an audio waveform using a vocoder like HiFiGAN. The model was trained to produce high-quality, natural-sounding speech.
Compared to similar TTS models like XTTS-v2 and speecht5_tts, the tts-tacotron2-ljspeech model is focused specifically on English text-to-speech generation using the Tacotron2 architecture, while the other models offer more multilingual capabilities or additional tasks like speech translation.
Model inputs and outputs
Inputs
- Text: The model accepts text input, which it then converts to a spectrogram.
Outputs
- Spectrogram: The model outputs a spectrogram representation of the generated speech.
- Alignment: The model also outputs an alignment matrix, which shows the relationship between the input text and the generated spectrogram.
Capabilities
The tts-tacotron2-ljspeech model is capable of generating high-quality, natural-sounding English speech from text input. It can capture features like prosody and intonation, resulting in speech that sounds more human-like compared to simpler text-to-speech systems.
What can I use it for?
You can use the tts-tacotron2-ljspeech model to add text-to-speech capabilities to your applications, such as:
- Voice assistants: Integrate the model into a voice assistant to allow users to interact with your application using natural language.
- Audiobook generation: Generate high-quality audio narrations from text, such as for creating digital audiobooks.
- Language learning: Use the model to provide pronunciations and examples of spoken English for language learners.
Things to try
One interesting aspect of the tts-tacotron2-ljspeech model is its ability to capture prosody and intonation in the generated speech. Try experimenting with different types of input text, such as sentences with various punctuation or emotional tone, to see how the model handles them. You can also try combining the model with a vocoder like HiFiGAN to generate the final audio waveform and listen to the results.
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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