metadata

language: ary
metrics:
  - wer
tags:
  - audio
  - automatic-speech-recognition
  - speech
  - xlsr-fine-tuning-week
license: apache-2.0
model-index:
  - name: XLSR Wav2Vec2 Moroccan Arabic dialect by Boumehdi
    results:
      - task:
          name: Speech Recognition
          type: automatic-speech-recognition
        metrics:
          - name: Test WER
            type: wer
            value: 44.3

Wav2Vec2-Large-XLSR-53-Moroccan-Darija

wav2vec2-large-xlsr-53 fine-tuned on 8.5 hours of labeled Darija Audios

I have also added 3 phonetic units to this model ڭ, ڤ and پ. For example: ڭال , ڤيديو , پودكاست

Usage

The model can be used directly (without a language model) as follows:

import librosa
import torch
from transformers import Wav2Vec2CTCTokenizer, Wav2Vec2ForCTC, Wav2Vec2Processor, TrainingArguments, Wav2Vec2FeatureExtractor, Trainer

tokenizer = Wav2Vec2CTCTokenizer("./vocab.json", unk_token="[UNK]", pad_token="[PAD]", word_delimiter_token="|")
processor = Wav2Vec2Processor.from_pretrained('boumehdi/wav2vec2-large-xlsr-moroccan-darija', tokenizer=tokenizer)
model=Wav2Vec2ForCTC.from_pretrained('boumehdi/wav2vec2-large-xlsr-moroccan-darija')


# load the audio data (use your own wav file here!)
input_audio, sr = librosa.load('file.wav', sr=16000)

# tokenize
input_values = processor(input_audio, return_tensors="pt", padding=True).input_values

# retrieve logits
logits = model(input_values).logits

tokens=torch.argmax(logits, axis=-1)

# decode using n-gram
transcription = tokenizer.batch_decode(tokens)

# print the output
print(transcription)

Here's the output: ڭالت ليا هاد السيد هادا ما كاينش بحالو

Evaluation & Previous works

-v2 (fine-tuned on 8.5 hours of audio + replaced أ and ى and إ with ا as it creates a lot of problems + tried to standardize the Moroccan Darija)

Wer: 44.30

Training Loss: 12.99

Validation Loss: 36.93

#############################################################

-v1 (fine-tuned on 6 hours of audio)

Wer: 49.68

Training Loss: 9.88

Validation Loss: 45.24

Future Work

I am currently working on improving this model. The new model will be available soon.

email: souregh@gmail.com