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---
language:
- is
library_name: nemo
datasets:
- samromur
- samromur_children
- malromur
- althingi
thumbnail: null
tags:
- automatic-speech-recognition
- speech
- audio
- CTC
- pytorch
- NeMo
- QuartzNet
- QuartzNet15x5
- icelandic
license: cc-by-4.0
widget:
model-index:
- name: stt_is_quartznet15x5_ft_ep56_875h
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: Samrómur (Test)
type: language-and-voice-lab/samromur_asr
split: test
args:
language: is
metrics:
- name: WER
type: wer
value: 28.56
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: Samrómur (Dev)
type: language-and-voice-lab/samromur_asr
split: validation
args:
language: is
metrics:
- name: WER
type: wer
value: 25.10
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: Samrómur Children (Test)
type: language-and-voice-lab/samromur_children
split: test
args:
language: is
metrics:
- name: WER
type: wer
value: 32.51
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: Samrómur Children (Dev)
type: language-and-voice-lab/samromur_children
split: validation
args:
language: is
metrics:
- name: WER
type: wer
value: 21.99
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: Malrómur (Test)
type: language-and-voice-lab/malromur_asr
split: test
args:
language: is
metrics:
- name: WER
type: wer
value: 22.88
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: Malrómur (Dev)
type: language-and-voice-lab/malromur_asr
split: validation
args:
language: is
metrics:
- name: WER
type: wer
value: 22.82
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: Althingi (Test)
type: althingi_test
split: test
args:
language: is
metrics:
- name: WER
type: wer
value: 20.74
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: Althingi (Dev)
type: althingi_dev
split: validation
args:
language: is
metrics:
- name: WER
type: wer
value: 20.68
---
# stt_is_quartznet15x5_ft_ep56_875h
**NOTE! This model was trained with the NeMo version: nemo-toolkit==1.10.0**
The "stt_is_quartznet15x5_ft_ep56_875h" is an acoustic model created with NeMo which is suitable for Automatic Speech Recognition in Icelandic.
It is the result of fine-tuning the model ["QuartzNet15x5Base-En.nemo"](https://catalog.ngc.nvidia.com/orgs/nvidia/models/nemospeechmodels/files) with around 875 hours of Icelandic data developed by the [Language and Voice Laboratory](https://huggingface.co/language-and-voice-lab). Most of the data is available at public repositories such as [LDC](https://www.ldc.upenn.edu/) or [OpenSLR](https://openslr.org/)
The specific list of corpora used to fine-tune the model is:
- [Samrómur 21.05 (114h34m)](http://www.openslr.org/112/)
- [Samrómur Children (127h25m)](https://catalog.ldc.upenn.edu/LDC2022S11)
- [Malrómur (119hh03m)](https://clarin.is/en/resources/malromur/)
- [Althingi Parliamentary Speech (514h29m)](https://catalog.ldc.upenn.edu/LDC2021S01)
The fine-tuning process was performed during September (2022) in the servers of the Language and Voice Laboratory (https://lvl.ru.is/) at Reykjavík University (Iceland) by Carlos Daniel Hernández Mena.
```bibtex
@misc{mena2022quartznet15x5icelandic,
title={Acoustic Model in Icelandic: stt_is_quartznet15x5_ft_ep56_875h.},
author={Hernandez Mena, Carlos Daniel},
year={2022},
url={https://huggingface.co/carlosdanielhernandezmena/stt_is_quartznet15x5_ft_ep56_875h},
}
```
# Acknowledgements
Special thanks to Jón Guðnason, head of the Language and Voice Lab for providing computational power to make this model possible. We also want to thank to the "Language Technology Programme for Icelandic 2019-2023" which is managed and coordinated by Almannarómur, and it is funded by the Icelandic Ministry of Education, Science and Culture.
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