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pipeline.py

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+
+import whisper
+from transformers import WhisperProcessor, WhisperForConditionalGeneration
+from googletrans import Translator
+import torch
+
+def load_models():
+    lang_detector = whisper.load_model("small")
+    tamil_processor = WhisperProcessor.from_pretrained("Lingalingeswaran/whisper-small-ta")
+    tamil_model = WhisperForConditionalGeneration.from_pretrained("Lingalingeswaran/whisper-small-ta")
+    sinhala_processor = WhisperProcessor.from_pretrained("Lingalingeswaran/whisper-small-sinhala")
+    sinhala_model = WhisperForConditionalGeneration.from_pretrained("Lingalingeswaran/whisper-small-sinhala")
+    english_model = whisper.load_model("small")
+    return lang_detector, tamil_processor, tamil_model, sinhala_processor, sinhala_model, english_model
+
+def detect_language(audio_file, lang_detector):
+    audio = whisper.load_audio(audio_file)
+    audio = whisper.pad_or_trim(audio)
+    mel = whisper.log_mel_spectrogram(audio).to(lang_detector.device)
+    _, probs = lang_detector.detect_language(mel)
+    return max(probs, key=probs.get)
+
+def transcribe_audio(audio_file, detected_lang, tamil_processor, tamil_model, sinhala_processor, sinhala_model, english_model):
+    if detected_lang == "ta":
+        processor, model = tamil_processor, tamil_model
+    elif detected_lang == "si":
+        processor, model = sinhala_processor, sinhala_model
+    else:
+        model = english_model
+        return model.transcribe(audio_file)["text"]
+
+    audio = whisper.load_audio(audio_file)
+    inputs = processor(audio, return_tensors="pt", sampling_rate=16000)
+    with torch.no_grad():
+        predicted_ids = model.generate(**inputs)
+    return processor.batch_decode(predicted_ids, skip_special_tokens=True)[0]
+
+def translate_to_english(text):
+    return Translator().translate(text, dest="en").text
+
+def full_pipeline(audio_file):
+    lang_detector, tamil_processor, tamil_model, sinhala_processor, sinhala_model, english_model = load_models()
+    detected_lang = detect_language(audio_file, lang_detector)
+    transcription = transcribe_audio(audio_file, detected_lang, tamil_processor, tamil_model, sinhala_processor, sinhala_model, english_model)
+    return translate_to_english(transcription)