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This project transforms analytical insights into an AI-generated “street interview” with Arsenal manager Mikel Arteta. Using multiple TTS and AI video tools, both an audio interview and a Wavel AI–generated video with subtitles and football stock footage were produced.

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gauravyadav-git/AI-Generated-Street-Interview-with-a-Premier-League-Manager

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Research Task 06 – AI Street Interview (Premier League 2022–23)

📌 Overview

This project is Research Task 06, which builds on earlier work from Task 05 part 1 and part 2.

  • In Task 05 - part 1, I analyzed the Premier League 2022–23 dataset without grouping, generated descriptive statistics for the first 10 rows, designed LLM prompts, and compared AI responses with Python results.
  • In Task 05 - part 2, I extended the analysis to the full dataset by grouping by stadium, producing pivot-style summaries, targeted visualizations, and Python scripts for more complex queries.

Task 06 takes a creative turn by applying those insights to an AI-generated “street interview” with Arsenal manager Mikel Arteta, reflecting on team performance during the 2022–23 season and looking ahead to the future.


🏟 Task 06 Objective

  • Create a street interview script based on dataset insights (Task 05 focus: no grouping).
  • Generate AI audio interview with distinct voices for interviewer and manager.
  • Document multiple approaches attempted, including failures and final workflow.
  • Deliver a final merged audio interview simulating a realistic media interaction.

📂 Repository Contents

File Name Description
script.txt Interview script used as input for audio/video generation.
Task_06_Street_Interview.mp3 Final merged audio interview (from Narakeet + Clideo).
Mikel Arteta Discusses Arsenal's Progress and Aspirations-mp4 Final video interview (Wavel AI) with subtitles and stock footage.
experiments/ Documentation of all attempts (ChatGPT, Gemini, ElevenLabs, Narakeet, Wavel AI).
├── README.md Detailed log of experiments and outcomes.
├── chatgpt_attempts.txt Notes from ChatGPT/Gemini trials.
├── elevenlabs_attempts.txt Notes from voice cloning test.
├── narakeet_clips/ 10 generated audio clips before merging.
└── clideo_merge.txt Notes on merging Narakeet clips into one audio file.

🛠 Workflow & Approaches

Tools Explored

  1. ChatGPT → Could not generate audio/video, but suggested other tools.
  2. Gemini AI → No audio/video interview support.
  3. ElevenLabs → Successful voice cloning of Arteta using sample from voicy.network, but full TTS required paid subscription.
  4. Narakeet → Generated 10 separate clips (Interviewer + Arteta).
  5. Clideo.com → Merged clips into single interview.
  6. Python (pydub) → Attempted merging locally, but required FFmpeg installation. Not pursued.
  7. WavelAI → Generated a video Interview.

✅ Final Workflow

  1. Drafted street interview script (Interviewer + Mikel Arteta).
  2. Tested multiple platforms (ChatGPT, Gemini, ElevenLabs, Narakeet).
  3. Produced audio-only interview with Narakeet + Clideo.
  4. Produced a video interview with Wavel AI, including auto-subtitles and contextual football clips.

📊 Reflection

This task demonstrated:

  • How analytical insights can be transformed into narrative storytelling.
  • The process of evaluating and troubleshooting multiple AI tools (balancing free vs. paid features).
  • How different platforms add different value:
    • Narakeet gave controlled dialogue (audio only).
    • Wavel AI added creativity, recent football references, and stock visuals for a realistic video.

The final result is a combination of audio and video deliverables, showing both technical adaptability and creative application of AI tools.


About

This project transforms analytical insights into an AI-generated “street interview” with Arsenal manager Mikel Arteta. Using multiple TTS and AI video tools, both an audio interview and a Wavel AI–generated video with subtitles and football stock footage were produced.

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