Automatic Speech Recognition
NeMo
speech-recognition
speech-to-text
stt
transcription
speech
audio
asr
arabic
arabic-asr
arabic-speech
dialectal-arabic
msa
modern-standard-arabic
gulf-arabic
egyptian-arabic
levantine-arabic
maghrebi-arabic
multi-dialect
nemo-toolkit
nvidia
fastconformer
fastconformer-ctc
conformer
ctc
efficient
lightweight
compact
on-device
edge
cpu-inference
real-time
low-latency
low-resource
Eval Results (legacy)
Instructions to use lemuralabs/lemura-arabic-asr-lite with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- NeMo
How to use lemuralabs/lemura-arabic-asr-lite with NeMo:
import nemo.collections.asr as nemo_asr asr_model = nemo_asr.models.ASRModel.from_pretrained("lemuralabs/lemura-arabic-asr-lite") transcriptions = asr_model.transcribe(["file.wav"]) - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 946c6968424d80bfa3e17156f77d54f140018dfac82074c521def0585a2ac766
- Size of remote file:
- 438 MB
- SHA256:
- adfcd84f595abeea89fe0dc1de9df13a458b524787015612188949ff11dd9812
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.