Automatic Speech Recognition
NeMo
Finnish
asr
speech-recognition
canary-v2
kenlm
finnish
Eval Results (legacy)
Instructions to use RASMUS/Finnish-ASR-Canary-v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- NeMo
How to use RASMUS/Finnish-ASR-Canary-v2 with NeMo:
import nemo.collections.asr as nemo_asr asr_model = nemo_asr.models.ASRModel.from_pretrained("RASMUS/Finnish-ASR-Canary-v2") transcriptions = asr_model.transcribe(["file.wav"]) - Notebooks
- Google Colab
- Kaggle
| Dataset Creation Tool Based on CTC-Segmentation | |
| =============================================== | |
| This tool provides functionality to align long audio files with the corresponding transcripts and split them into shorter fragments | |
| that are suitable for an Automatic Speech Recognition (ASR) model training. | |
| More details could be found in `NeMo/tutorials/tools/CTC_Segmentation_Tutorial.ipynb <https://colab.research.google.com/github/NVIDIA/NeMo/blob/stable/tutorials/tools/CTC_Segmentation_Tutorial.ipynb>`__ (can be executed with `Google's Colab <https://colab.research.google.com/notebooks/intro.ipynb>`_). | |
| The tool is based on the `CTC-Segmentation <https://github.com/lumaku/ctc-segmentation>`__ package and | |
| `CTC-Segmentation of Large Corpora for German End-to-end Speech Recognition | |
| <https://arxiv.org/abs/2007.09127>`__ :cite:`tools-kurzinger2020ctc` | |
| References | |
| ---------- | |
| .. bibliography:: tools_all.bib | |
| :style: plain | |
| :labelprefix: TOOLS | |
| :keyprefix: tools- | |