de-coder/stt_sw_ctc_model
Model Overview
<DESCRIBE IN ONE LINE THE MODEL AND ITS USE>
NVIDIA NeMo: Training
To train, fine-tune or play with the model you will need to install NVIDIA NeMo. We recommend you install it after you've installed latest Pytorch version.
pip install nemo_toolkit['all']How to Use this Model
The model is available for use in the NeMo toolkit [3], and can be used as a pre-trained checkpoint for inference or for fine-tuning on another dataset.
Automatically instantiate the model
import nemo.collections.asr as nemo_asr
asr_model = nemo_asr.models.ASRModel.from_pretrained("decoder/STT_SW_Model")Transcribing using Python
First, let's get a samples of three different files
!wget https://rapidshare.io/2oUF/common_voice_sw_27777611.wav
!wget https://rapidshare.io/2oUG/common_voice_sw_27777627.wav
!wget https://rapidshare.io/2oUH/common_voice_sw_27791961.wav
Then simply do: if in colab
transcriptions = asr_model.transcribe(["/content/common_voice_sw_27777611.wav"])Transcribing many audio files
python [NEMO_GIT_FOLDER]/examples/asr/transcribe_speech.py pretrained_name="de-coder/stt_rw_conformer_ctc_large" audio_dir="<DIRECTORY CONTAINING AUDIO FILES>"Input
This model accepts 16000 KHz Mono-channel Audio (wav files) as input.
Output
This model provides transcribed speech as a string for a given audio sample.
Model Architecture
<ADD SOME INFORMATION ABOUT THE ARCHITECTURE>
Training
<ADD INFORMATION ABOUT HOW THE MODEL WAS TRAINED - HOW MANY EPOCHS, AMOUNT OF COMPUTE ETC>
Datasets
<LIST THE NAME AND SPLITS OF DATASETS USED TO TRAIN THIS MODEL (ALONG WITH LANGUAGE AND ANY ADDITIONAL INFORMATION)>
Performance
<LIST THE SCORES OF THE MODEL - OR USE THE Hugging Face Evaluate LiBRARY TO UPLOAD METRICS>
Limitations
<DECLARE ANY POTENTIAL LIMITATIONS OF THE MODEL>
Eg: Since this model was trained on publically available speech datasets, the performance of this model might degrade for speech which includes technical terms, or vernacular that the model has not been trained on. The model might also perform worse for accented speech.
References
<ADD ANY REFERENCES HERE AS NEEDED>