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Model Overview

VITS is an flow-based parallel end-to-end speech synthesis model. It consists of 2 encoders: TextEncoder and PosteriorEncoder (for spectrograms), normalizing flow, duration predictor and HiFiGAN vocoder.

During training, TextEncoder produces representation of text tokens and PosteriorEncoder produces representation of spectrograms are then fed to normalizing flow. This two representatons are then trained to match with KL divergence as in VAE. Also spectrogram representation are fed to MAS block to produce labels for Duration Predictor training.

During inference, Duration Predictor generates alignments from noise with conditioning on TextEncoder representations. Then they are passed through inversed flow to Vocoder block, which generates audios.

Training

This model is trained on HiFiTTS sampled at 41000Hz, and has been tested on generating male and female English voices with an American accent.

Performance

No performance information available at this time.

How to Use this Model

# Load VITS\nfrom nemo.collections.tts.models import VitsModel\naudio_generator = VitsModel.from_pretrained(\"tts_en_hifitts_vits\")\n\n# Generate audio\nimport soundfile as sf\nimport torch\nwith torch.no_grad():\n    parsed = audio_generator.parse(\"You can type your sentence here to get nemo to produce speech.\")\n    audio = audio_generator.convert_text_to_waveform(tokens=parsed)\n\n# Save the audio to disk in a file called speech.wav\nif isinstance(audio, torch.Tensor):\n    audio = audio.to('cpu').numpy()\nsf.write(\"speech.wav\", audio.T, 41000, format=\"WAV\")\n

Input

This model accepts batches of text.

Output

This model outputs audio at 44100Hz.

Limitations

There are no known limitations at this time.

Versions

1.15.0 (current): The original version released with NeMo 1.15.0.

References

VITS paper: https://arxiv.org/abs/2106.06103
\ngithub: https://github.com/jaywalnut310/vits

Licence

License to use this model is covered by the NGC TERMS OF USE unless another License/Terms Of Use/EULA is clearly specified. By downloading the public and release version of the model, you accept the terms and conditions of the NGC TERMS OF USE.

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It consists of 2 encoders: TextEncoder and PosteriorEncoder (for spectrograms), normalizing flow, duration predictor and HiFiGAN vocoder.\n \nDuring training, TextEncoder produces representation of text tokens and PosteriorEncoder produces representation of spectrograms are then fed to normalizing flow. This two representatons are then trained to match with KL divergence as in VAE. Also spectrogram representation are fed to MAS block to produce labels for Duration Predictor training. \n\nDuring inference, Duration Predictor generates alignments from noise with conditioning on TextEncoder representations. Then they are passed through inversed flow to Vocoder block, which generates audios.\n\n## Training\n\nThis model is trained on HiFiTTS sampled at 41000Hz, and has been tested on generating male and female English voices with an American accent.\n\n## Performance\n\nNo performance information available at this time.\n\n## How to Use this Model\n\n```python\n# Load VITS\nfrom nemo.collections.tts.models import VitsModel\naudio_generator = VitsModel.from_pretrained(\"tts_en_hifitts_vits\")\n\n# Generate audio\nimport soundfile as sf\nimport torch\nwith torch.no_grad():\n parsed = audio_generator.parse(\"You can type your sentence here to get nemo to produce speech.\")\n audio = audio_generator.convert_text_to_waveform(tokens=parsed)\n\n# Save the audio to disk in a file called speech.wav\nif isinstance(audio, torch.Tensor):\n audio = audio.to('cpu').numpy()\nsf.write(\"speech.wav\", audio.T, 41000, format=\"WAV\")\n```\n### Input\n\nThis model accepts batches of text.\n\n\n### Output\n\nThis model outputs audio at 44100Hz.\n\n## Limitations\n\nThere are no known limitations at this time.\n\n## Versions\n\n1.15.0 (current): The original version released with NeMo 1.15.0.\n\n## References\n\nVITS paper: [https://arxiv.org/abs/2106.06103](https://arxiv.org/abs/2106.06103) \ngithub: [https://github.com/jaywalnut310/vits](https://github.com/jaywalnut310/vits) \n## Licence\n\nLicense to use this model is covered by the NGC [TERMS OF USE](https://ngc.nvidia.com/legal/terms) unless another License/Terms Of Use/EULA is clearly specified. 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As part of our bot management service, this cookie helps manage incoming traffic that matches criteria associated with bots.\nThis is a CloudFoundry cookie","OptanonConsent","nvid.nvidia.com","This cookie is set by the cookie compliance solution from OneTrust. It stores information about the categories of cookies the site uses and whether visitors have given or withdrawn consent for the use of each category. This enables site owners to prevent cookies in each category from being set in the users browser, when consent is not given. The cookie has a normal lifespan of one year, so that returning visitors to the site will have their preferences remembered. It contains no information that can identify the site visitor.","events.nvidia.com","This cookie is associated with the Amazon Web Services Elastic Load Balancing functionality for routing client request on the server.Used to attribute commission to affiliates when you arrive at the website from an affiliate referral link. It is set when you click on one of our links and used to let the advertiser and us know the website from which you came.","sessionid","This is a very generic cookie name that may have different purposes on different sites, but generally it will be some kind of anonymous session identifier.","_csrf","This cookie is used to prevent Cross-Site Request Forgery (CSRF) attacks, ensuring that each request made to the server is from the user's browser and is intentional.","enterprise-support.nvidia.com","Used to apply end-user cookie consent preferences set by our client-side utility.Custom- Short Duration. Unique ID of an Enquiry- used to validate access to case, and load exisiting data.\n","renderCtx","academicgrants.nvidia.com","Used to store site parameters in the session for reuse across requests by a single client for functionality and performance reasons.","ph_phc_yQgAEdJJkVpI24NdSRID2mor1x1leRpDoC9yZ9mfXal_posthog","The PostHog ph_phc_xxx cookie is a session cookie used for identifying and tracking visitors on websites, helping us understand user behavior and website performance.","This cookie is managed by AWS and is used for load balancing.Used to attribute commission to affiliates when you arrive at the website from an affiliate referral link. It is set when you click on one of our links and used to let the advertiser and us know the website from which you came.","This cookie is associated with Akamai and is used to differentiate between traffic from humans and bots.","OptanonAlertBoxClosed","docs.ngc.nvidia.com","This cookie is set by websites using certain versions of the cookie law compliance solution from OneTrust. It is set after visitors have seen a cookie information notice and in some cases only when they actively close the notice down. It enables the website not to show the message more than once to a user. The cookie has a normal lifespan of one year and contains no personal information.","nv_co","__uxq412__ses.88c1","investor.nvidia.com","learn.learn.nvidia.com","This cookie is associated with the Amazon Web Services Elastic Load Balancing functionality for routing client request on the server.","pctrk","Used to count page views by unauthenticated users against license usage.","bm_s","bpazaws52gukakzc__ctrl0_ctl36_uccaptcha","bm_sv","store.nvidia.com","The __cf_bm cookie is a cookie necessary to support Cloudflare Bot Management, currently in private beta. 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It is set when you click on one of our links and used to let the advertiser and us know the website from which you came.","_devzone_session","This cookie is likely used to maintain a user session on the website by the server. It is common for session identifiers to be used to keep users logged in and track their interaction with the site during a session.","_cs_c","The cookie is used by Content Square to save the user consent to be tracked.","bm_sz","This cookie is used by Akamai to optimize site performance and security. It is typically associated with the delivery of web content and services.","vcalliance.nvidia.com","ASP.NET_SessionId","General purpose platform session cookie, used by sites written with Microsoft .NET based technologies. 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