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dc.contributor.author Lebar Bajec, Iztok
dc.contributor.author Bajec, Marko
dc.contributor.author Bajec, Žan
dc.date.accessioned 2022-12-02T10:48:01Z
dc.date.available 2022-12-02T10:48:01Z
dc.date.issued 2022-12-01
dc.identifier.uri http://hdl.handle.net/11356/1740
dc.description Automated Speech Recognition service for NeMo Conformer CTC BPE E2E models. For more details about building such models, see the official NVIDIA NeMo documentation (https://docs.nvidia.com/deeplearning/nemo/user-guide/docs/en/stable/asr/intro.html) and NVIDIA NeMo GitHub (https://github.com/NVIDIA/NeMo). A model for automated speech recognition of Slovene speech can be downloaded from http://hdl.handle.net/11356/1740. The service accepts as input audio files in WAV 16kHz, 16bit PCM, mono format. The maximal accepted audio duration is 300s. Note that transcription of one 300s audio file on cpu will take advantage of all available cores, consume up to 16GB RAM and may take ~180s (on a system with 24 vCPU). See the service README.md for further details.
dc.publisher Faculty of Computer and Information Science, University of Ljubljana
dc.relation.isreferencedby https://rsdo.slovenscina.eu/en/speech-technologies
dc.rights Apache License 2.0
dc.rights.uri https://opensource.org/licenses/Apache-2.0
dc.rights.label PUB
dc.source.uri https://github.com/clarinsi/Slovene_ASR_e2e
dc.subject speech recognition
dc.subject NeMo
dc.subject service
dc.title NeMo Conformer CTC BPE E2E Automated Speech Recognition service RSDO-DS2-ASR-E2E-API 1.1
dc.type toolService
metashare.ResourceInfo#ContentInfo.detailedType service
metashare.ResourceInfo#ResourceComponentType#ToolServiceInfo.languageDependent false
has.files yes
branding CLARIN.SI data & tools
contact.person Iztok Lebar Bajec ilb@fri.uni-lj.si Faculty of Computer and Information Science, University of Ljubljana
sponsor Ministry of Culture C3340-20-278001 Development of Slovene in a Digital Environment Other
files.count 1
files.size 40960


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