Text to Speech

TTS, Text-To-Speech or Speech Synthesis refers to the problem of getting a program to generate human voice output output from text. TAO Toolkit supports a two-stage pipeline for TTS:

A spectrogram model to generate a Mel spectrogram from text (FastPitch)
A vocoder model to generate audio from a Mel spectrogram (HiFiGAN)

Our goal here is to generate FastPitch and HiFiGAN model, that when cascaded generates a good quality human voice from text.

The best place to get started with TAO Toolkit - TTS would be the TAO - TTS jupyter notebooks sample enclosed in this sample.\nThis resource has three notebooks included.

Training: Sample workflow for training FastPitch spectrogram generator model and a HiFiGAN vocoder model and export them to a .riva file
Finetuning: Sample workflow to finetune a FastPitch spectrogram generator model and a HiFiGAN vocoder model from another pretrained FastPitch and HiFiGAN model.
Deployment: Sample workflow to consume the .riva files and deploy it to Riva.

If you are a seasoned Conversation AI developer we recommend installing TAO and referring to the TAO documentation for detailed information.

Pre-Requisites

Please make sure to install the following before proceeding further:

python 3.6.9
python-dev
docker-ce > 19.03.5
docker-API 1.40
nvidia-container-toolkit > 1.3.0-1
nvidia-container-runtime > 3.4.0-1
nvidia-docker2 > 2.5.0-1
nvidia-driver >= 455.23

Note: A compatible NVIDIA GPU would be required.

Installation

We recommend that you install TAO Toolkit inside a virtual environment. The steps to do the same are as follows

\nsource /bin/activate\npip install jupyter notebook # If you need to run the notebooks\n\">

virtualenv -p python3 <name of venv>\nsource <name of venv>/bin/activate\npip install jupyter notebook # If you need to run the notebooks\n

TAO Toolkit is a python package that is hosted in nvidia python package index. You may install by using python’s package manager, pip.

pip install nvidia-pyindex\npip install nvidia-tao\n

To download the jupyter notebook please:

Download the samples using the ngc cli with the following command

ngc registry resource download-version \"nvidia/tao/texttospeech_notebook:v1.1\"\n

Instantiate the jupyter notebook server

jupyter notebook --ip 0.0.0.0 --allow-root --port 8888\n

License

By downloading and using the models and resources packaged with TAO Toolkit Conversational AI, you would be accepting the terms of the Riva license

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TAO Toolkit supports a two-stage pipeline for TTS:\n\n1. A spectrogram model to generate a Mel spectrogram from text (FastPitch)\n2. A vocoder model to generate audio from a Mel spectrogram (HiFiGAN)\n\nOur goal here is to generate FastPitch and HiFiGAN model, that when cascaded generates a good quality human voice from text.\n\nThe best place to get started with TAO Toolkit - TTS would be the TAO - TTS jupyter notebooks sample enclosed in this sample.\nThis resource has three notebooks included.\n\n1. Training: Sample workflow for training FastPitch spectrogram generator model and a HiFiGAN vocoder model and export them to a `.riva` file\n2. Finetuning: Sample workflow to finetune a FastPitch spectrogram generator model and a HiFiGAN vocoder model from another pretrained FastPitch and HiFiGAN model.\n3. Deployment: Sample workflow to consume the `.riva` files and deploy it to Riva.\n\nIf you are a seasoned Conversation AI developer we recommend installing TAO and referring to the [TAO documentation](https://docs.nvidia.com/tao/tao-toolkit/text/overview.html) for detailed information.\n\n## Pre-Requisites\n\nPlease make sure to install the following before proceeding further:\n\n* python 3.6.9\n* python-dev\n* docker-ce > 19.03.5\n* docker-API 1.40\n* nvidia-container-toolkit > 1.3.0-1\n* nvidia-container-runtime > 3.4.0-1\n* nvidia-docker2 > 2.5.0-1\n* nvidia-driver >= 455.23\n\n*Note: A compatible NVIDIA GPU would be required.*\n\n## Installation\n\nWe recommend that you install TAO Toolkit inside a virtual environment. The steps to do the same are as follows \n\n```sh\nvirtualenv -p python3 \nsource /bin/activate\npip install jupyter notebook # If you need to run the notebooks\n```\n\nTAO Toolkit is a python package that is hosted in nvidia python package index. You may install by using python’s package manager, pip.\n\n```sh\npip install nvidia-pyindex\npip install nvidia-tao\n```\n\nTo download the jupyter notebook please:\n\n1. Download the samples using the ngc cli with the following command\n\n ```sh\n ngc registry resource download-version \"nvidia/tao/texttospeech_notebook:v1.1\"\n ```\n\n2. Instantiate the jupyter notebook server\n\n ```sh\n jupyter notebook --ip 0.0.0.0 --allow-root --port 8888\n ```\n\n## License\n\nBy downloading and using the models and resources packaged with TAO Toolkit Conversational AI, you would be accepting the terms of the Riva [license](https://developer.nvidia.com/riva/ga/license)","displayName","Text to Speech Notebook",["D",1680632257986],"publisher","NVIDIA","latestVersion","collectionCounts","imageUrl","/api/image/nvidia/tao/resources/texttospeech_notebook","rawImageUrl","https://dz112fgwz7ogh.cloudfront.net/logos/Nvidia-Centric-TAO-RIVA.png","canGuestDownload","latestVersionSizeInBytes","licenseTerms","isMultinodeEnabled","isMultiArchitecture","bias","explainability","privacy","safetyAndSecurity","featureLabels",[],"displayLabels",[308,309,310,311,312],"policyLabels",[],"systemLabels",[],"products",[],"hasNimMetadata",{"_277":329,"_314":329,"_315":330,"_317":88},{"_277":327,"_314":327,"_315":328,"_317":88},{"_277":323,"_314":324,"_315":325,"_317":88},{"_277":319,"_314":320,"_315":321,"_317":88},{"_277":313,"_314":313,"_315":316,"_317":88},"Transfer Learning","value","filter",{"_318":88,"_314":313},"category","field","Text to Speech","uscs_text_to_speech",{"_318":322,"_314":320},"application","Inference","soln_inference",{"_318":326,"_314":324},"technology","HiFiGAN",{"_318":88,"_314":327},"FastPitch",{"_318":88,"_314":329},{"_180":1308,"_182":1309},"ngcApps",[1261],"csaApiBaseUrl","https://www.nvidia.com/ai-agents/csa-agent/dcsm","datadogRum",{"_1242":1243,"_1244":1245,"_1246":1247,"_1248":1249,"_1250":342,"_110":366,"_1251":1252,"_1253":60,"_1254":91,"_1255":91,"_1256":1257,"_1258":91,"_1259":1260},"amplitude",{"_1239":1240,"_879":-7,"_1241":35},"disableJs","environment","prod","featureFlagsBlob","JTdCJTIydGVzdEZsYWclMjIlM0FmYWxzZSUyQyUyMnNob3dTZWFyY2hMYWJlbFNldEZpbHRlcnMlMjIlM0FmYWxzZSUyQyUyMmVuYWJsZUNzYVdpZGdldCUyMiUzQWZhbHNlJTJDJTIyZW5hYmxlUHJvZHVjdEdyb3VwaW5nQnlTdWJzY3JpcHRpb24lMjIlM0FmYWxzZSUyQyUyMmNvbnRhaW5lclNjYW5uaW5nUmVkZXNpZ25NMSUyMiUzQXRydWUlN0Q=","featureFlagsGuarded","isDevLikeEnv","isPlaywright","isMobileDevice","categorizedOrgs",{"_1233":1234,"_1235":1236,"_1237":1238},"currentOrgContext","currentContextRoles",[],"enterpriseOrgs",[],"locale","en","ngcApiOrigin","ngcHelmOrigin","origin","https://catalog.ngc.nvidia.com","usesMocks","theme","year",2026,"1.10.0","defaultSearchSuggestions",{"_1119":447,"_1120":1121,"_1122":1123,"_1124":1125},"announcements",[],"consentState",{"_404":1109,"_1110":35,"_1111":35,"_1112":91,"_1113":1114},"consentConfig",{"_386":387,"_388":389,"_390":391,"_392":393,"_394":395,"_396":397,"_398":399,"_400":401,"_402":403,"_404":405},"showContactAdmin",1784816516762,[],[],[380,381,382,383,384,385],{"_49":64,"_51":74,"_53":175,"_55":-5,"_57":-5,"_59":60},{"_49":64,"_51":71,"_53":175,"_55":-5,"_57":-5,"_59":60},{"_49":64,"_51":69,"_53":175,"_55":-5,"_57":-5,"_59":60},{"_49":64,"_51":65,"_53":175,"_55":-5,"_57":-5,"_59":60},{"_49":61,"_51":62,"_53":54,"_55":56,"_57":63,"_59":60},{"_49":50,"_51":52,"_53":175,"_55":-5,"_57":-5,"_59":60},"mainInfoText","We and our third-party partners (including social media, advertising, and analytics partners) use cookies and other tracking technologies to collect, store, monitor, and process certain information about you when you visit our website. 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	Files	Compressed Size
v1.3.0Selected	4	168.4 KB	January 4, 2023 UTC
v1.2.1	4	156.05 KB	September 15, 2022 UTC
v1.2.0	4	156.04 KB	June 2, 2022 UTC
v1.1.1	3	232.73 KB	May 18, 2022 UTC
v1.1	2	50.56 KB	April 7, 2022 UTC
v1.0	2	35.89 KB	November 23, 2021 UTC