Punctuation and Capitalization

Automatic Speech Recognition (ASR) systems typically generate text with no punctuation and capitalization of the words. This tutorial explains how to train a model that will predict punctuation and capitalization for each word in a sentence, thereby making the ASR output more readable and boosting the performance of the named entity recognition, machine translation or text-to-speech models. In this sample, we start by using a pre-trained BERT model. For every word in our training dataset we’re going to predict:

Punctuation mark that should follow the words.
Whether the word should be capitalized.

The best place to get started with TAO Toolkit - Punctuation and Capitalization would be the TAO - Punctuation and Capitalization jupyter notebook. This resource has two notebooks included.

Training: Sample workflow for training a punctuation capitalization model and export the model to a .riva file
Deployment: Sample workflow to consume the .riva file and deploy it to Riva.

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

Pre-Requisites

Please make sure to install the following before proceeding further:

python 3.6.9
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.

virtualenv -p python3 \nsource /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/punctuationcapitalization_notebook:v1.0\"\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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This tutorial explains how to train a model that will predict punctuation and capitalization for each word in a sentence, thereby making the ASR output more readable and boosting the performance of the named entity recognition, machine translation or text-to-speech models. In this sample, we start by using a pre-trained BERT model. For every word in our training dataset we’re going to predict:\n\n* Punctuation mark that should follow the words.\n* Whether the word should be capitalized.\n\nThe best place to get started with TAO Toolkit - Punctuation and Capitalization would be the TAO - Punctuation and Capitalization jupyter notebook. This resource has two notebooks included.\n\n1. Training: Sample workflow for training a punctuation capitalization model and export the model to a `.riva` file\n2. Deployment: Sample workflow to consume the `.riva` file 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 usage information.\n\n## Pre-Requisites\n\nPlease make sure to install the following before proceeding further:\n\n* python 3.6.9\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\nngc registry resource download-version \"nvidia/tao/punctuationcapitalization_notebook:v1.0\"\n```\n\n2. Instantiate the jupyter notebook server\n\n```sh\njupyter 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)","Punctuation Capitalization Notebook",["D",1680632542459],"/api/image/nvidia/tao/resources/punctuationcapitalization_notebook","https://dz112fgwz7ogh.cloudfront.net/logos/Nvidia-Centric-TAO-RIVA.png",25521,"bias","explainability","privacy","safetyAndSecurity",[],[265,266,267,268,269,270,271],[],[],[],{"_90":286,"_123":286,"_124":287,"_126":127},{"_90":284,"_123":284,"_124":285,"_126":127},{"_90":129,"_123":129,"_124":283,"_126":127},{"_90":279,"_123":280,"_124":281,"_126":127},{"_90":275,"_123":276,"_124":277,"_126":127},{"_90":273,"_123":273,"_124":274,"_126":127},{"_90":122,"_123":122,"_124":272,"_126":127},{"_128":127,"_123":122},"Punctuation",{"_128":127,"_123":273},"Natural Language Understanding","uscs_natural_language_understanding",{"_128":278,"_123":276},"application","Inference","soln_inference",{"_128":282,"_123":280},"technology",{"_128":127,"_123":129},"Capitalization",{"_128":127,"_123":284},"BERT",{"_128":127,"_123":286},{"_157":1459,"_159":1460},"ngcApps",[1412],"csaApiBaseUrl","https://www.nvidia.com/ai-agents/csa-agent/dcsm","datadogRum",{"_1393":1394,"_1395":1396,"_1397":1398,"_1399":1400,"_1401":299,"_189":323,"_1402":1403,"_1404":51,"_1405":136,"_1406":136,"_1407":1408,"_1409":136,"_1410":1411},"amplitude",{"_1390":1391,"_997":-7,"_1392":26},"disableJs","environment","prod","featureFlagsBlob","JTdCJTIydGVzdEZsYWclMjIlM0FmYWxzZSUyQyUyMnNob3dTZWFyY2hMYWJlbFNldEZpbHRlcnMlMjIlM0FmYWxzZSUyQyUyMmNoaW5hTmltRGlzdHJpYnV0b3JzUmVkZXNpZ24lMjIlM0F0cnVlJTJDJTIyZW5hYmxlQ3NhV2lkZ2V0JTIyJTNBZmFsc2UlMkMlMjJlbmFibGVQcm9kdWN0R3JvdXBpbmdCeVN1YnNjcmlwdGlvbiUyMiUzQWZhbHNlJTJDJTIyY29udGFpbmVyU2Nhbm5pbmdSZWRlc2lnbk0xJTIyJTNBdHJ1ZSU3RA==","featureFlagsGuarded","isDevLikeEnv","isPlaywright","isMobileDevice","categorizedOrgs",{"_1384":1385,"_1386":1387,"_1388":1389},"currentOrgContext","currentContextRoles",[],"enterpriseOrgs",[],"locale","en","ngcApiOrigin","ngcHelmOrigin","origin","https://catalog.ngc.nvidia.com","usesMocks","theme","year",2026,"1.7.3","defaultSearchSuggestions",{"_1272":405,"_1273":1274,"_1275":1276,"_1277":1278},"announcements",[],"consentState",{"_362":1262,"_1263":136,"_1264":26,"_1265":26,"_1266":1267},"consentConfig",{"_344":345,"_346":347,"_348":349,"_350":351,"_352":353,"_354":355,"_356":357,"_358":359,"_360":361,"_362":363},"showContactAdmin",1784147465703,[],[],[337,338,339,340,341,342],{"_40":54,"_42":65,"_44":152,"_46":-5,"_48":-5,"_50":51},{"_40":54,"_42":63,"_44":152,"_46":-5,"_48":-5,"_50":51},{"_40":54,"_42":61,"_44":152,"_46":-5,"_48":-5,"_50":51},{"_40":54,"_42":59,"_44":152,"_46":-5,"_48":-5,"_50":51},{"_40":52,"_42":53,"_44":152,"_46":-5,"_48":-5,"_50":51},{"_40":41,"_42":43,"_44":45,"_46":47,"_48":343,"_50":51},4,"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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