fish-speech-1.4
Maintainer: fishaudio
310
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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
fish-speech-1.4 is a leading text-to-speech (TTS) model developed by fishaudio. It is trained on over 700k hours of audio data across multiple languages, including English, Chinese, German, Japanese, French, Spanish, Korean, and Arabic. This makes it one of the most comprehensive multilingual TTS models available. In comparison, earlier versions like [object Object] and [object Object] were trained on smaller datasets of 300k and 150k hours respectively, focusing primarily on English, Chinese, and Japanese.
Model inputs and outputs
fish-speech-1.4 is a text-to-speech model, taking text input and generating high-quality audio output. The model supports a wide range of languages, allowing users to generate speech in their language of choice.
Inputs
- Text in one of the supported languages: English, Chinese, German, Japanese, French, Spanish, Korean, or Arabic
Outputs
- Synthesized audio in the corresponding language
Capabilities
fish-speech-1.4 is capable of generating highly natural-sounding speech across multiple languages. The model leverages extensive training data and advanced deep learning techniques to produce realistic intonation, rhythm, and timbre. This makes it suitable for a variety of applications, from text-to-speech assistants to audio book narration.
What can I use it for?
fish-speech-1.4 can be used in a wide range of applications that require text-to-speech functionality. This includes virtual assistants, audiobook creation, language learning tools, and multimedia content production. The model's multilingual capabilities make it particularly useful for reaching global audiences or creating content in multiple languages.
Things to try
One interesting aspect of fish-speech-1.4 is its ability to handle code-switching between languages. This means the model can generate speech that seamlessly transitions between different languages within the same audio, which can be useful for content creators working with multilingual audiences. Experimenting with this feature can lead to unique and engaging audio 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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