Automatic Speech Recognition

ASR, or Automatic Speech Recognition, refers to the problem of getting a program to automatically transcribe spoken language (speech-to-text). Our goal is usually to have a model that minimizes the Word Error Rate (WER) metric when transcribing speech input. In other words, given some audio file (e.g. a WAV file) containing speech.

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

Training: Sample workflow for training an ASR - Citrinet 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 detailed 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

\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/speechtotext_citrinet_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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Our goal is usually to have a model that minimizes the Word Error Rate (WER) metric when transcribing speech input. In other words, given some audio file (e.g. a WAV file) containing speech.\n\nThe best place to get started with TAO Toolkit - ASR would be the TAO - ASR jupyter notebooks sample enclosed in this sample.\nThis resource has two notebooks included.\n\n1. Training: Sample workflow for training an ASR - Citrinet 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 detailed 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/speechtotext_citrinet_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)","Speech to Text Citrinet Notebook",["D",1680631685415],"/api/image/nvidia/tao/resources/speechtotext_citrinet_notebook","https://dz112fgwz7ogh.cloudfront.net/logos/Nvidia-Centric-TAO-RIVA.png",12959,"bias","explainability","privacy","safetyAndSecurity",[],[270,271,272,273,274],[],[],[],{"_91":283,"_124":284,"_125":285,"_127":128},{"_91":281,"_124":281,"_125":282,"_127":128},{"_91":130,"_124":130,"_125":280,"_127":128},{"_91":276,"_124":277,"_125":278,"_127":128},{"_91":123,"_124":123,"_125":275,"_127":128},{"_129":128,"_124":123},"Inference","soln_inference",{"_129":279,"_124":277},"technology",{"_129":128,"_124":130},"Citrinet",{"_129":128,"_124":281},"Automatic Speech Recognition","uscs_automatic_speech_recognition",{"_129":286,"_124":284},"application",{"_158":1265,"_160":1266},"ngcApps",[1218],"csaApiBaseUrl","https://www.nvidia.com/ai-agents/csa-agent/dcsm","datadogRum",{"_1199":1200,"_1201":1202,"_1203":1204,"_1205":1206,"_1207":298,"_189":324,"_1208":1209,"_1210":51,"_1211":137,"_1212":137,"_1213":1214,"_1215":137,"_1216":1217},"amplitude",{"_1196":1197,"_838":-7,"_1198":26},"disableJs","environment","prod","featureFlagsBlob","JTdCJTIydGVzdEZsYWclMjIlM0FmYWxzZSUyQyUyMnNob3dTZWFyY2hMYWJlbFNldEZpbHRlcnMlMjIlM0FmYWxzZSUyQyUyMmVuYWJsZUNzYVdpZGdldCUyMiUzQWZhbHNlJTJDJTIyZW5hYmxlUHJvZHVjdEdyb3VwaW5nQnlTdWJzY3JpcHRpb24lMjIlM0FmYWxzZSUyQyUyMmNvbnRhaW5lclNjYW5uaW5nUmVkZXNpZ25NMiUyMiUzQWZhbHNlJTdE","featureFlagsGuarded","isDevLikeEnv","isPlaywright","isMobileDevice","categorizedOrgs",{"_1190":1191,"_1192":1193,"_1194":1195},"currentOrgContext","currentContextRoles",[],"enterpriseOrgs",[],"manageableExternalUserGroups",[],"ngcApiOrigin","ngcHelmOrigin","origin","https://catalog.ngc.nvidia.com","usesMocks","theme","year",2026,"now",1789381417805,"1.15.0","defaultSearchSuggestions",{"_1078":405,"_1079":1080,"_1081":1082,"_1083":1084},"announcements",[],"consentState",{"_362":1068,"_1069":137,"_1070":26,"_1071":26,"_1072":1073},"consentConfig",{"_344":345,"_346":347,"_348":349,"_350":351,"_352":353,"_354":355,"_356":357,"_358":359,"_360":361,"_362":363},"showContactAdmin",1789381417806,[],[],[338,339,340,341,342,343],{"_40":55,"_42":65,"_44":63,"_46":-5,"_48":-5,"_50":51},{"_40":55,"_42":64,"_44":63,"_46":-5,"_48":-5,"_50":51},{"_40":55,"_42":60,"_44":63,"_46":-5,"_48":-5,"_50":51},{"_40":55,"_42":56,"_44":63,"_46":-5,"_48":-5,"_50":51},{"_40":52,"_42":53,"_44":63,"_46":-5,"_48":-5,"_50":51},{"_40":41,"_42":43,"_44":63,"_46":-5,"_48":-5,"_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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