Presentation Analyzer [Speak Your Mind]

We can grade emotions, gesture-use, & textual content generated from a video of a speech and then generate pointers to improve on each >of these categories.

• Emotions of the Presenter are mirrored by the audience; therefore, gauging how the presenter is speaking (stress, anxiety, etc.) ⇒ Hume AI can do this as well

• Spoken Content needs to be parsed into something we can process textually ⇒ some sort of speech-to-text API for converting the spoken language into a speech

  • Google likely has some APIs for thisTextual Content can be analyzed for correctness, delivery, ⇒ LLM from Grammarly or GPT or Claude for understanding and grading the content of the speech for accuracy

• Together AI has an open LLM to use (w/ LLaMa), but we have to ensure that payment isn’t crazy

  • https://developer.grammarly.com/docs/writing-suggestions

• Body Language is an essential part of the speaker’s appearance on stage and therefore reception in the audience ⇒ analyzing hand gestures, posture, eye contact, etc. would be powerful to users

  • Lol no idea how to do this, should be CV libraries that can accomplish this but how tf
  • May have to be a part of next steps

• We can study the qualitative aspects that good presenters possess, creating heuristics for analyzing the metrics we gauge

  • Rank certain emotions as +/- based on the qualitative study
  • Qualify certain textual content [words, phrases, slang, etc.] as +/ based on great speeches’ content
  • Classify body language/movements as +/- based on speed of movement, position, etc.
  • Gauge speed, stutter, & clarity of speech and associate with +/- i mpact on speech quality

Next Steps

• Audience Analysis: we could analyze audience emotion to gauge how they react to the speeches given (i.e. we can record the live audience in an actual speech; Ted Talks, etc. are good resources for this)

• Eventually, we can leverage this to predict how an audience would respond to a given speech, thereby providing a more thorough analysis of audience reception to the speech content, body language, and emotions of the presenter’s specific video

Elevator Pitch

Names

• Speak Your Mind
• SymPresent / PresentSym
• GhostWriter

Use-Cases

• For those with learning disabilities, social anxiety, social disorders, etc. our product helps overcome these limitations through targeted practice

  • Not just any kind of practice, but practice that helps YOU get better
  • Can be fine-tuned by the person, helping anyone get tips that concentrate on their specific weaknesses

• Similarly, for anyone who’s afraid of speaking, this is a tool that helps break down some of the stress of public speaking through practice

  • Again, fine-tuned to the person so we can better suggest pointers, etc.
  • It’s like a speech coach that knows everything about speaking

• For companies who want to analyze consumer responses to product roll-outs Apple, etc. launch products, they may want real-time analysis for the audience reactions and which products excite the people most interested in their product

• For audience analysis as a whole, we can eventually roll-out features for specific audiences (fan-bases, general audience, etc. can all be analyzed to create datasets based on their propensity for certain behaviors)

  • Again, can be used to see how audiences would react to product announcements based on the speech, textual, and emotional content of an advertisement

• For research purposes, it’ll be useful to have a way to collect data about audiences and behavior on a large scale when influenced by a single (or multiple) speaker(s)

  • Can conduct case studies on the impact of certain emotions and gestures on audience retention, etc. ⇒ political science, sociology research

  • Can use this dataset to avoid heuristics when grading the users, instead relying on real-world data

  • We can justify the user of heuristics for now since we our audience members ourselves and we conducted a qualitative study, but in the future quantifiable proof would be preferred

Plan

Pipeline

Web App

Backend Frontend