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8f3666f | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 | #!/usr/bin/env python3
"""Transcribe one Urdu call-audio file with PakUrdu-Conversational-ASR-r12.
Usage:
python inference_example.py call.wav [more.wav ...]
Loads the public base model from the HF hub, applies this LoRA adapter,
merges, and decodes with the certified settings (language=ur, greedy).
"""
import sys
import soundfile as sf
import torch
from peft import PeftModel
from transformers import WhisperForConditionalGeneration, WhisperProcessor
BASE = "openai/whisper-large-v3-turbo"
ADAPTER = "KhiredNetworks/PakUrdu-Conversational-ASR"
if len(sys.argv) < 2:
sys.exit(__doc__)
processor = WhisperProcessor.from_pretrained(BASE)
model = WhisperForConditionalGeneration.from_pretrained(BASE)
model = PeftModel.from_pretrained(model, ADAPTER).merge_and_unload()
for path in sys.argv[1:]:
speech, sr = sf.read(path, dtype="float32")
if speech.ndim > 1:
speech = speech.mean(axis=1)
inputs = processor(speech, sampling_rate=sr, return_tensors="pt")
with torch.no_grad():
ids = model.generate(inputs.input_features, language="ur",
task="transcribe", do_sample=False)
text = processor.batch_decode(ids, skip_special_tokens=True)[0].strip()
print(f"{path}: {text}")
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