High-Level Design Document

Title: AI-Driven Localized Newscast System

  1. Project Overview

    • Objective: Develop an AI-driven newscast system capable of generating localized news videos for any given zip code. • Target Audience: Local residents interested in comprehensive news coverage specific to their region.

  2. System Components

    • Input Module: Interface for users to input a zip code. • Data Aggregation Engine: • Fetches and categorizes news into segments: local, state, national, international, weather, and traffic. • Data Sources: News APIs, weather and traffic information services. • Content Generation and Processing: • AI Script Generation: Summarizes news into scripts for each segment. • Text-to-Speech (TTS) System: Converts scripts into audio. • AI Anchor Generation: Creates virtual news anchors for each segment using tools like Synthesia. • Visual Asset Creation: Generates relevant visuals and graphics using AI tools like DALL-E. • Video Production Engine: • Combines audio, AI anchor visuals, and graphical assets into a cohesive video. • Editing Tools: Adobe Premiere Pro, DaVinci Resolve, or AI-driven editors. • Output Module: Distributes the final newscast video.

  3. Technology Stack

    • Web Scraping: Python (BeautifulSoup, Scrapy) • AI Script Writing: GPT-4 • Text-to-Speech: Google Cloud Text-to-Speech, Amazon Polly • AI Avatars: Synthesia • AI Art Generation: DALL-E • Video Editing: Adobe Premiere Pro, DaVinci Resolve • Web Development: HTML, CSS, JavaScript • Server Backend: Node.js, Python Flask or Django

  4. Key Features

    • Dynamic content generation for any zip code. • Comprehensive news coverage including various segments. • Customizable AI anchors for different news segments. • Integrated weather and traffic updates. • User-friendly web interface for input and viewing.

Detailed Process Flow

1.	User Input
•	User enters a zip code on the system’s interface.
2.	Data Aggregation
•	System queries APIs and online sources for news, weather, and traffic relevant to the zip code.
•	Data is categorized into segments: local, state, national, international, weather, and traffic.
3.	Script Generation for Each Segment
•	AI creates scripts for different segments: Headline News, Weather, Traffic, Sports, Health, Entertainment, and Special Segments.
4.	Narration and Avatar Creation
•	Scripts are narrated using TTS technology.
•	AI-generated avatars are tailored for each segment:
•	Main News Anchor: Confident, articulate, professional.
•	Weather Reporter: Approachable, friendly.
•	Traffic Reporter: Practical, efficient.
•	Sports Anchor: Lively, enthusiastic.
•	Health Correspondent: Compassionate, informative.
•	Entertainment Reporter: Charismatic, engaging.
•	Field Reporters: Adaptable to segment tone.
5.	Visual Asset Generation
•	AI tools create visuals and graphics for each news segment.
6.	Video Assembly
•	Combines TTS audio, AI anchor visuals, and graphics for each segment.
•	News segments are edited into a complete newscast.
7.	Output and Distribution
•	Final newscast video is rendered and made available to the user.
8.	Feedback and Iteration
•	Collect user feedback for continuous improvement of the system.

This design and process flow provide a detailed roadmap for creating an AI-driven newscast system that delivers tailored news content based on a specific zip code, with diverse segments and AI-generated anchors.