metadata
library_name: Nvidia Nemo
license: apache-2.0
language:
- fa
pipeline_tag: automatic-speech-recognition
tags:
- Persian
- Neura
- PersianASR
datasets:
- common_voice_17_0
Neura Speech Nemo
Model Description
- Developed by: Neura company
- Funded by: Neura
- Model type: fa_FastConformers_Transducer
- Language(s) (NLP): Persian
Model Architecture
The model features an improved Conformer architecture from Fast Conformer with Linearly Scalable Attention for Efficient Speech Recognition.
Uses
Check out the Google Colab demo to run NeuraSpeech ASR on a free-tier Google Colab instance: 
make sure these packages are installed:
!pip install nemo_toolkit['all']
from IPython.display import Audio, display
display(Audio('persian_audio.mp3', rate = 32_000,autoplay=True))
import nemo
print('nemo', nemo.__version__)
import numpy as np
import nemo.collections.asr as nemo_asr
asr_model = nemo_asr.models.EncDecRNNTBPEModel.from_pretrained(model_name="Neurai/NeuraSpeech_900h")
asr_model.transcribe(paths2audio_files=['persian_audio.mp3', ], batch_size=1)[0]
trascribed text :
او خواهان آزاد کردن بردگان بود
More Information
Model Card Authors
Esmaeil Zahedi, Mohsen Yazdinejad