MARS5-TTS
Maintainer: CAMB-AI
391
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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
MARS5-TTS is a novel speech model developed by CAMB-AI that can generate high-quality speech with impressive prosody. Unlike traditional text-to-speech (TTS) models, MARS5 follows a two-stage pipeline with a distinctly novel non-autoregressive (NAR) component. This architecture allows the model to generate speech even for prosodically challenging scenarios like sports commentary and anime. With just 5 seconds of audio and a snippet of text, MARS5 can produce speech that captures the nuances and emotional expression of the input.
Model inputs and outputs
MARS5 is a text-to-speech model that takes in text and a reference audio file to generate synthetic speech. The model can be fine-tuned to a specific speaker's voice by providing a longer reference audio clip.
Inputs
- Text transcript
- Optional: Reference audio file (2-12 seconds, with 6 seconds being optimal)
Outputs
- Synthetic speech audio
Capabilities
MARS5 can generate high-quality, expressive speech that captures the prosody and emotional tone of the input text and reference audio. The model's novel NAR architecture enables it to handle diverse speech scenarios like sports commentary and anime, which tend to have more complex prosodic patterns than typical TTS use cases.
What can I use it for?
MARS5-TTS is well-suited for a variety of text-to-speech applications, such as audiobook narration, podcast creation, and virtual assistant voice production. The ability to fine-tune the model to a specific speaker's voice also makes it useful for dubbing and voice cloning applications. Additionally, the model's strong prosodic capabilities make it a good fit for generating speech for video game characters, animated films, and other media that requires expressive, natural-sounding dialogue.
Things to try
One interesting aspect of MARS5 is its ability to be guided by the input text formatting, such as using punctuation and capitalization to control the prosody of the generated speech. Try experimenting with different formatting techniques in the text transcript to see how they impact the final audio output. Additionally, providing a high-quality reference audio clip can help the model better capture the desired speaker's voice and speaking style.
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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MARS5-TTS is a novel speech model developed by CAMB-AI that can generate high-quality speech with impressive prosody. Unlike traditional text-to-speech (TTS) models, MARS5 follows a two-stage pipeline with a distinctly novel non-autoregressive (NAR) component. This architecture allows the model to generate speech even for prosodically challenging scenarios like sports commentary and anime. With just 5 seconds of audio and a snippet of text, MARS5 can produce speech that captures the nuances and emotional expression of the input. Model inputs and outputs MARS5 is a text-to-speech model that takes in text and a reference audio file to generate synthetic speech. The model can be fine-tuned to a specific speaker's voice by providing a longer reference audio clip. Inputs Text transcript Optional: Reference audio file (2-12 seconds, with 6 seconds being optimal) Outputs Synthetic speech audio Capabilities MARS5 can generate high-quality, expressive speech that captures the prosody and emotional tone of the input text and reference audio. The model's novel NAR architecture enables it to handle diverse speech scenarios like sports commentary and anime, which tend to have more complex prosodic patterns than typical TTS use cases. What can I use it for? MARS5-TTS is well-suited for a variety of text-to-speech applications, such as audiobook narration, podcast creation, and virtual assistant voice production. The ability to fine-tune the model to a specific speaker's voice also makes it useful for dubbing and voice cloning applications. Additionally, the model's strong prosodic capabilities make it a good fit for generating speech for video game characters, animated films, and other media that requires expressive, natural-sounding dialogue. Things to try One interesting aspect of MARS5 is its ability to be guided by the input text formatting, such as using punctuation and capitalization to control the prosody of the generated speech. Try experimenting with different formatting techniques in the text transcript to see how they impact the final audio output. Additionally, providing a high-quality reference audio clip can help the model better capture the desired speaker's voice and speaking style.
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