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",[],[267,268,269,270,271,272,273],[],[],[],{"_91":288,"_124":288,"_125":289,"_127":128},{"_91":286,"_124":286,"_125":287,"_127":128},{"_91":130,"_124":130,"_125":285,"_127":128},{"_91":281,"_124":282,"_125":283,"_127":128},{"_91":277,"_124":278,"_125":279,"_127":128},{"_91":275,"_124":275,"_125":276,"_127":128},{"_91":123,"_124":123,"_125":274,"_127":128},{"_129":128,"_124":123},"Punctuation",{"_129":128,"_124":275},"Natural Language Understanding","uscs_natural_language_understanding",{"_129":280,"_124":278},"application","Inference","soln_inference",{"_129":284,"_124":282},"technology",{"_129":128,"_124":130},"Capitalization",{"_129":128,"_124":286},"BERT",{"_129":128,"_124":288},{"_159":1268,"_161":1269},"ngcApps",[1221],"csaApiBaseUrl","https://www.nvidia.com/ai-agents/csa-agent/dcsm","datadogRum",{"_1202":1203,"_1204":1205,"_1206":1207,"_1208":1209,"_1210":301,"_191":327,"_1211":1212,"_1213":51,"_1214":137,"_1215":137,"_1216":1217,"_1218":137,"_1219":1220},"amplitude",{"_1199":1200,"_841":-7,"_1201":26},"disableJs","environment","prod","featureFlagsBlob","JTdCJTIydGVzdEZsYWclMjIlM0FmYWxzZSUyQyUyMnNob3dTZWFyY2hMYWJlbFNldEZpbHRlcnMlMjIlM0FmYWxzZSUyQyUyMmVuYWJsZUNzYVdpZGdldCUyMiUzQWZhbHNlJTJDJTIyZW5hYmxlUHJvZHVjdEdyb3VwaW5nQnlTdWJzY3JpcHRpb24lMjIlM0FmYWxzZSUyQyUyMmNvbnRhaW5lclNjYW5uaW5nUmVkZXNpZ25NMiUyMiUzQWZhbHNlJTdE","featureFlagsGuarded","isDevLikeEnv","isPlaywright","isMobileDevice","categorizedOrgs",{"_1193":1194,"_1195":1196,"_1197":1198},"currentOrgContext","currentContextRoles",[],"enterpriseOrgs",[],"manageableExternalUserGroups",[],"ngcApiOrigin","ngcHelmOrigin","origin","https://catalog.ngc.nvidia.com","usesMocks","theme","year",2026,"now",1789344313060,"1.15.0","defaultSearchSuggestions",{"_1081":409,"_1082":1083,"_1084":1085,"_1086":1087},"announcements",[],"consentState",{"_366":1071,"_1072":137,"_1073":26,"_1074":26,"_1075":1076},"consentConfig",{"_348":349,"_350":351,"_352":353,"_354":355,"_356":357,"_358":359,"_360":361,"_362":363,"_364":365,"_366":367},"showContactAdmin",1789344313061,[],[],[341,342,343,344,345,346,347],{"_40":55,"_42":66,"_44":154,"_46":-5,"_48":-5,"_50":51},{"_40":55,"_42":64,"_44":154,"_46":-5,"_48":-5,"_50":51},{"_40":55,"_42":62,"_44":154,"_46":-5,"_48":-5,"_50":51},{"_40":55,"_42":60,"_44":154,"_46":-5,"_48":-5,"_50":51},{"_40":55,"_42":56,"_44":154,"_46":-5,"_48":-5,"_50":51},{"_40":52,"_42":53,"_44":154,"_46":-5,"_48":-5,"_50":51},{"_40":41,"_42":43,"_44":45,"_46":47,"_48":54,"_50":51},"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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