Serialtechlab/mms-trilingual-dv-ar-en-v2

MMS Trilingual ASR v2 - Dhivehi + Arabic + English

Fine-tuned version of mms-trilingual-dv-ar-en with improved:

• Conversational Arabic recognition (FLEURS Arabic)
• Melodic Dhivehi (Madhaha/podcasts) recognition

Changes from v1

• Added conversational Arabic data (FLEURS) to replace Quranic-only training
• Added melodic Dhivehi (audio casts) to fix Madhaha confusion with Arabic
• Removed Quranic recitation data

Training Data

• Arabic: ~2500 samples from FLEURS (conversational)
• Dhivehi Melodic: 1000 samples from audio casts
• Dhivehi Normal: ~1500 samples
• English: ~500 samples from LibriSpeech

Performance

• Final WER: 0.2820

Usage

from transformers import AutoProcessor, Wav2Vec2ForCTC
import torch

processor = AutoProcessor.from_pretrained("Serialtechlab/mms-trilingual-dv-ar-en-v2")
model = Wav2Vec2ForCTC.from_pretrained("Serialtechlab/mms-trilingual-dv-ar-en-v2")

# Process audio (16kHz)
inputs = processor(audio_array, sampling_rate=16000, return_tensors="pt")

with torch.no_grad():
    logits = model(**inputs).logits

predicted_ids = torch.argmax(logits, dim=-1)
transcription = processor.batch_decode(predicted_ids)[0]

Supported Languages

• Dhivehi (Thaana script) - including melodic/Madhaha
• Arabic (Arabic script) - conversational style
• English (Latin script)