Upload speach_text.py

speach_text.py

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+import streamlit as st
+import whisper
+import tempfile
+import os
+
+st.title("🎙️ Audio to SRT Transcription App (Whisper)")
+
+uploaded_file = st.file_uploader("Upload an audio file", type=["mp3", "wav", "m4a"])
+
+if uploaded_file is not None:
+    with tempfile.NamedTemporaryFile(delete=False, suffix=".wav") as tmpfile:
+        file_path = tmpfile.name
+        tmpfile.write(uploaded_file.read())
+
+    st.audio(uploaded_file, format="audio/wav")
+
+    # Load Whisper model
+    model = whisper.load_model("large")  # Change to "medium" or "large" for better accuracy
+
+    # Transcribe
+    result = model.transcribe(file_path)
+
+    # Save as SRT
+    srt_path = file_path.replace(".wav", ".srt")
+    with open(srt_path, "w") as srt_file:
+        for i, segment in enumerate(result["segments"]):
+            start = segment["start"]
+            end = segment["end"]
+            text = segment["text"]
+            srt_file.write(f"{i+1}\n{start:.3f} --> {end:.3f}\n{text}\n\n")
+
+    st.success("✅ Transcription Complete!")
+    st.text_area("Transcribed Text:", result["text"], height=200)
+
+    with open(srt_path, "rb") as srt_file:
+        st.download_button("📥 Download SRT File", srt_file, file_name="transcription.srt", mime="text/plain")
+
+    os.remove(file_path)
+    os.remove(srt_path)