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app.py

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+import librosa
+import gradio as gr
+from faster_whisper import WhisperModel
+
+class AudioToText:
+    """Converts an MP3 file to text using Faster Whisper."""
+
+    def __init__(self, model_size="medium.en", device="cpu", compute_type="int8", language="en"):
+        """Initialize the Whisper model for transcription."""
+        self.model = WhisperModel(model_size, device=device, compute_type=compute_type)
+        self.language = language
+
+    def transcribe_audio(self, file_path):
+        """Transcribe an MP3 audio file to text."""
+        audio, sr = librosa.load(file_path, sr=16000)
+        segments, _ = self.model.transcribe(audio, beam_size=5, language=self.language, vad_filter=True)
+        transcription = "\n".join([segment.text.strip() for segment in segments])
+        return transcription
+
+# Create an instance of the transcription model
+transcriber = AudioToText()
+
+# Define the Gradio function
+def transcribe_gradio(file_path):
+    return transcriber.transcribe_audio(file_path)
+
+# Create Gradio interface
+demo = gr.Interface(
+    fn=transcribe_gradio,
+    inputs=gr.Audio(type="filepath"),  # ✅ Fixed: Changed "file" to "filepath"
+    outputs="text",
+    title="Speech-to-Text Whisper Demo",
+    description="Upload an MP3 file to transcribe it to text using Faster Whisper.",
+)
+
+# Launch the demo
+demo.launch()
+

requirements.txt

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+gradio
+librosa
+faster-whisper