Discover Inspirational Insights in Motivational Sports Speeches Using
summary
A pipeline transcribes pre‑recorded sports speeches with the Deepgram Python SDK, extracts summaries, topics, and sentiment, and visualizes word clouds and sentiment bars using pandas and matplotlib. Topic detection flags Daryl Green as religion‑heavy, Kobe as win‑driven, Serena as the most positive with sentiment 44.4%, and Jimmy Valvano as emotionally cancer‑focused. A profanity filter removes curse words from transcripts. The JSON output is parsed and aggregated successfully, and a motivational routine claimed a real result: a team later beats its nemesis by 20 points.
AI-written summary · about
chapters (10)
- 0:00Motivational sports speeches
- 3:20Introduction
- 6:31Daryl Green’s Hall of Fame speech
- 8:38Kobe Bryant’s talk
- 10:29Serena Williams’ speech
- 12:20Jimmy Valvano’s ESPYs speech
- 14:26Sentiment analysis
- 19:30Profanity filter demo
- 21:36Inspiration overcoming rival
- 22:40Conclusion
related talks
35mDiscover Inspirational Insights in Motivational Sports Speeches Using Speech-to-Text
35mDecoding bias and narrative in competitive video games
42mHow Deep Learning is Revolutionizing Sports Analytics
39mSentiment Analysis, its techniques and applications
41mThe evolution of basketball with data science
39mTemporal Analysis on Topics Utilizing Word2Vec
56mSocial Listening, Data Extraction & Discovery
01h 05mSocial Text, Sentiment, and Tone Analysis
