August 20, 2019

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pmbaumgartner/syntax-speaker-prediction

pmbaumgartner/syntax-speaker-prediction

The tastiest machine learning project. Can we predict who is speaking for how long during an episode of the syntax.fm podcast?

repo name pmbaumgartner/syntax-speaker-prediction
repo link https://github.com/pmbaumgartner/syntax-speaker-prediction
homepage
language Jupyter Notebook
size (curr.) 11509 kB
stars (curr.) 36
created 2018-12-17
license

Syntax Speaker Prediction

This repository contains notebooks used to train a model to predict the speaker (Scott or Wes) in one second cilps of their podcast, syntax.fm. There are accompanying files for using Prodigy to label the data required to build the model. There is a brief description of the purpose of each notebook as the first cell.

The Results

Total Podcast Time: 3 days, 15 hours, 56 minutes, 39 seconds

Wes: 2 days, 1 hours, 51 minutes, 11 seconds

Scott: 1 days, 11 hours, 51 minutes, 45 seconds

Non-speaking time (crosstalk, laughing, intros): 0 days, 2 hours, 13 minutes, 43 seconds

Cumulative Speaking Time

Cumulative Speaking Time

Each vertical line is the start of a new episode.

Helpful tools:

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