Initial Commit

.gitignore

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+.env

README.md

@@ -1,7 +1,7 @@
 ---
 title: Moonshine Tiny STT
 emoji: 🏢
-colorFrom: green
+colorFrom: blue
 colorTo: red
 sdk: gradio
 sdk_version: 5.49.1

app.py

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+import gradio as gr
+import torchaudio
+from transformers import AutoModelForSpeechSeq2Seq, PreTrainedTokenizerFast
+
+from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq
+
+processor = AutoProcessor.from_pretrained("UsefulSensors/moonshine-tiny")
+model = AutoModelForSpeechSeq2Seq.from_pretrained("UsefulSensors/moonshine-tiny")
+tokenizer = PreTrainedTokenizerFast.from_pretrained("UsefulSensors/moonshine-tiny")
+
+
+def transcribe_audio(audio_path):
+    if audio_path is None:
+        return "Please provide an audio input."
+    
+    try:
+        # Load and resample audio
+        audio, sr = torchaudio.load(audio_path)
+        if sr != 16000:
+            audio = torchaudio.functional.resample(audio, sr, 16000)
+        
+        # Get transcription
+        tokens = model(audio)
+        transcription = tokenizer.decode(tokens[0], skip_special_tokens=True)
+        return transcription
+    except Exception as e:
+        return f"Error processing audio: {str(e)}"
+
+# Create Gradio interface
+with gr.Blocks() as demo:
+    gr.Markdown("## Audio Transcription App")
+    
+    with gr.Tabs():
+        with gr.TabItem("Upload Audio"):
+            audio_file = gr.Audio(
+                sources=["upload"],
+                type="filepath",
+                label="Upload Audio File"
+            )
+            output_text1 = gr.Textbox(
+                label="Transcription",
+                placeholder="Transcription will appear here..."
+            )
+            upload_button = gr.Button("Transcribe Uploaded Audio")
+            upload_button.click(
+                fn=transcribe_audio,
+                inputs=audio_file,
+                outputs=output_text1
+            )
+            
+        with gr.TabItem("Record Audio"):
+            audio_mic = gr.Audio(
+                sources=["microphone"],
+                type="filepath",
+                label="Record Audio"
+            )
+            output_text2 = gr.Textbox(
+                label="Transcription",
+                placeholder="Transcription will appear here..."
+            )
+            record_button = gr.Button("Transcribe Recorded Audio")
+            record_button.click(
+                fn=transcribe_audio,
+                inputs=audio_mic,
+                outputs=output_text2
+            )
+
+    gr.Markdown("""
+    ### Instructions:
+    1. Choose either 'Upload Audio' or 'Record Audio' tab
+    2. Upload an audio file or record using your microphone
+    3. Click the respective 'Transcribe' button
+    4. Wait for the transcription to appear
+    """)
+
+if __name__ == "__main__":
+    demo.launch()