Mancinni.mp4 — Mm - Samuel Decker & Lucas

# Configure API request audio_config = speech.RecognitionConfig( encoding=speech.RecognitionConfig.AudioEncoding.MP4, sample_rate_hertz=16000, language_code="en-US", )

# Make API request response = speech_client.recognize(config=audio_config, audio=audio) MM - Samuel Decker & Lucas Mancinni.mp4

# Example usage video_file = "MM - Samuel Decker & Lucas Mancinni.mp4" print(generate_transcript(video_file)) This example focuses on Google Cloud services for transcript generation. You would need to adapt it based on your tech stack and requirements. Implementing the full feature set described would require significant development, including front-end UI, back-end API, and possibly machine learning model training for summary generation. # Configure API request audio_config = speech

audio = speech.RecognitionAudio(uri=f"gs://{bucket_name}/{video_file}") including front-end UI

from google.cloud import speech from google.cloud import storage import io

# Process response transcript = "" for result in response.results: transcript += result.alternatives[0].transcript