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],[],[],[],{"_89":288,"_122":288,"_123":289,"_125":126},{"_89":286,"_122":286,"_123":287,"_125":126},{"_89":128,"_122":128,"_123":285,"_125":126},{"_89":281,"_122":282,"_123":283,"_125":126},{"_89":277,"_122":278,"_123":279,"_125":126},{"_89":275,"_122":275,"_123":276,"_125":126},{"_89":121,"_122":121,"_123":274,"_125":126},{"_127":126,"_122":121},"Punctuation",{"_127":126,"_122":275},"Natural Language Understanding","uscs_natural_language_understanding",{"_127":280,"_122":278},"application","Inference","soln_inference",{"_127":284,"_122":282},"technology",{"_127":126,"_122":128},"Capitalization",{"_127":126,"_122":286},"BERT",{"_127":126,"_122":288},{"_158":1263,"_160":1264},"ngcApps",[1216],"csaApiBaseUrl","https://www.nvidia.com/ai-agents/csa-agent/dcsm","datadogRum",{"_1197":1198,"_1199":1200,"_1201":1202,"_1203":1204,"_1205":301,"_190":327,"_1206":1207,"_1208":50,"_1209":135,"_1210":135,"_1211":1212,"_1213":135,"_1214":1215},"amplitude",{"_1194":1195,"_840":-7,"_1196":26},"disableJs","environment","prod","featureFlagsBlob","JTdCJTIydGVzdEZsYWclMjIlM0FmYWxzZSUyQyUyMnNob3dTZWFyY2hMYWJlbFNldEZpbHRlcnMlMjIlM0FmYWxzZSUyQyUyMmVuYWJsZUNzYVdpZGdldCUyMiUzQWZhbHNlJTJDJTIyZW5hYmxlUHJvZHVjdEdyb3VwaW5nQnlTdWJzY3JpcHRpb24lMjIlM0FmYWxzZSUyQyUyMmNvbnRhaW5lclNjYW5uaW5nUmVkZXNpZ25NMiUyMiUzQWZhbHNlJTdE","featureFlagsGuarded","isDevLikeEnv","isPlaywright","isMobileDevice","categorizedOrgs",{"_1188":1189,"_1190":1191,"_1192":1193},"currentOrgContext","currentContextRoles",[],"enterpriseOrgs",[],"manageableExternalUserGroups",[],"ngcApiOrigin","ngcHelmOrigin","origin","https://catalog.ngc.nvidia.com","usesMocks","theme","year",2026,"now",1787527527723,"1.12.0","defaultSearchSuggestions",{"_1080":408,"_1081":1082,"_1083":1084,"_1085":1086},"announcements",[],"consentState",{"_365":1070,"_1071":135,"_1072":26,"_1073":26,"_1074":1075},"consentConfig",{"_347":348,"_349":350,"_351":352,"_353":354,"_355":356,"_357":358,"_359":360,"_361":362,"_363":364,"_365":366},"showContactAdmin",1787527527725,[],[],[341,342,343,344,345,346],{"_39":54,"_41":63,"_43":64,"_45":-5,"_47":-5,"_49":50},{"_39":54,"_41":61,"_43":64,"_45":-5,"_47":-5,"_49":50},{"_39":54,"_41":59,"_43":64,"_45":-5,"_47":-5,"_49":50},{"_39":54,"_41":55,"_43":64,"_45":-5,"_47":-5,"_49":50},{"_39":51,"_41":52,"_43":44,"_45":46,"_47":53,"_49":50},{"_39":40,"_41":42,"_43":64,"_45":-5,"_47":-5,"_49":50},"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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