Speaker Diarization: TitaNet Model Card

Model Overview

TitaNet is a novel neural network architecture for extracting speaker representations.

Model Architecture

TitaNet employs 1D depth-wise separable convolutions with Squeeze-and-Excitation (SE) layers with global context followed by channel attention based statistics pooling layer to map variable-length utterances to a fixed-length embedding (t-vector) [1].

Training

These models were trained on a composite dataset comprising of several thousand hours of speech, compiled from various publicly available sources. The NeMo toolkit [2] was used for training this model over few hundred epochs on multiple GPUs.

How to Use this Model

To use this model, we can use Riva Skills Quick start guide, it is a starting point to try out Riva models. Information regarding Quick start guide can be found : here.\nTo use Riva Speech ASR service using this model, document has the necessary information.

Input

This model accepts 16000 KHz Mono-channel Audio (wav files) as input.

Output

This model provides embeddings of size 192 from a speaker for a given audio sample.

References

[1] TitaNet: Neural Model for speaker representation with 1D Depth-wise separable convolutions and global context\n[2] NVIDIA NeMo Toolkit

License

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

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The NeMo toolkit [2] was used for training this model over few hundred epochs on multiple GPUs.\n\n#### How to Use this Model\n\nTo use this model, we can use Riva Skills Quick start guide, it is a starting point to try out Riva models. Information regarding Quick start guide can be found : [here](https://ngc.nvidia.com/catalog/resources/nvidia:riva:riva_quickstart).\nTo use Riva Speech ASR service using this model, [document](https://docs.nvidia.com/deeplearning/riva/user-guide/docs/asr/asr-overview.html) has the necessary information.\n\n#### Input\n\nThis model accepts 16000 KHz Mono-channel Audio (wav files) as input.\n\n#### Output\n\nThis model provides embeddings of size 192 from a speaker for a given audio sample.\n\n#### References\n\n[1] [TitaNet: Neural Model for speaker representation with 1D Depth-wise separable convolutions and global context](https://arxiv.org/pdf/2110.04410.pdf)\n[2] [NVIDIA NeMo Toolkit](https://github.com/NVIDIA/NeMo)\n\n#### License\n\nBy downloading and using the models and resources packaged with Riva Conversational AI, you would be accepting the terms of the Riva [license](https://developer.nvidia.com/riva/ga/license)","RIVA Diarizer Embedding Extractor",["D",1680635824893],"deployable_v1.0","/api/image/nvidia/riva/models/diarizer_titanet_small","https://github.com/kbojo/images/raw/master/Nvidia-Centric-RIVA.png",37480408,"bias","explainability","privacy","safetyAndSecurity",[],[249,250,251,252,253],[],[],[],{"_92":261,"_128":261,"_129":262,"_131":132},{"_92":88,"_128":88,"_129":260,"_131":132},{"_92":258,"_128":258,"_129":259,"_131":132},{"_92":256,"_128":256,"_129":257,"_131":132},{"_92":254,"_128":254,"_129":255,"_131":132},"titanet",{"_133":132,"_128":254},"speaker recognition",{"_133":132,"_128":256},"speaker diarization",{"_133":132,"_128":258},{"_133":132,"_128":88},"asr",{"_133":132,"_128":261},{"_171":1244,"_173":1245},"ngcApps",[1197],"csaApiBaseUrl","https://www.nvidia.com/ai-agents/csa-agent/dcsm","datadogRum",{"_1178":1179,"_1180":1181,"_1182":1183,"_1184":1185,"_1186":274,"_203":302,"_1187":1188,"_1189":51,"_1190":214,"_1191":214,"_1192":1193,"_1194":214,"_1195":1196},"amplitude",{"_1175":1176,"_817":-7,"_1177":26},"disableJs","environment","prod","featureFlagsBlob","JTdCJTIydGVzdEZsYWclMjIlM0FmYWxzZSUyQyUyMnNob3dTZWFyY2hMYWJlbFNldEZpbHRlcnMlMjIlM0FmYWxzZSUyQyUyMmVuYWJsZUNzYVdpZGdldCUyMiUzQWZhbHNlJTJDJTIyZW5hYmxlUHJvZHVjdEdyb3VwaW5nQnlTdWJzY3JpcHRpb24lMjIlM0FmYWxzZSUyQyUyMmNvbnRhaW5lclNjYW5uaW5nUmVkZXNpZ25NMiUyMiUzQWZhbHNlJTdE","featureFlagsGuarded","isDevLikeEnv","isPlaywright","isMobileDevice","categorizedOrgs",{"_1169":1170,"_1171":1172,"_1173":1174},"currentOrgContext","currentContextRoles",[],"enterpriseOrgs",[],"manageableExternalUserGroups",[],"locale","en","ngcApiOrigin","ngcHelmOrigin","origin","https://catalog.ngc.nvidia.com","usesMocks","theme","year",2026,"now",1786048412820,"1.11.0","defaultSearchSuggestions",{"_1057":384,"_1058":1059,"_1060":1061,"_1062":1063},"announcements",[],"consentState",{"_340":1047,"_1048":214,"_1049":26,"_1050":26,"_1051":1052},"consentConfig",{"_322":323,"_324":325,"_326":327,"_328":329,"_330":331,"_332":333,"_334":335,"_336":337,"_338":339,"_340":341},"showContactAdmin",1786048412821,[],[],[316,317,318,319,320,321],{"_40":54,"_42":66,"_44":62,"_46":-5,"_48":-5,"_50":51},{"_40":54,"_42":63,"_44":62,"_46":-5,"_48":-5,"_50":51},{"_40":54,"_42":59,"_44":62,"_46":-5,"_48":-5,"_50":51},{"_40":54,"_42":55,"_44":62,"_46":-5,"_48":-5,"_50":51},{"_40":52,"_42":53,"_44":62,"_46":-5,"_48":-5,"_50":51},{"_40":41,"_42":43,"_44":62,"_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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users logged in across NVIDIA domains.","api.ngc.nvidia.com","This cookie is managed by AWS and is used for load balancing.","bm_so","This cookie name is used to load the site as quickly as possible and to recognize bots using Akamai.","The __cf_bm cookie is a cookie necessary to support Cloudflare Bot Management, currently in private beta. 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It is set when you click on one of our links and used to let the advertiser and us know the website from which you came.","This cookie is associated with Akamai and is used to differentiate between traffic from humans and bots.","nv_co","__uxq412__ses.88c1","learn.learn.nvidia.com","This cookie is associated with the Amazon Web Services Elastic Load Balancing functionality for routing client request on the server.","pctrk","Used to count page views by unauthenticated users against license usage.","bm_s","bpazaws52gukakzc__ctrl0_ctl36_uccaptcha","bm_sv","store.nvidia.com","The __cf_bm cookie is a cookie necessary to support Cloudflare Bot Management, currently in private beta. 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