Unlocking More From Your Audio Data

Braden Riggs

Prior knowledge:
No previous knowledge expected

Summary

We'll discuss a recent project to explore some of the audio data and what it means in being an insightful judge of quality. Using Python staples such as Matplotlib can give us a visualization to complement these insights in the world of podcasts when dealing with content production on large collections of media. The team recommended that I resubmit as a lightning talk.

Description

With increasing demand to consume and create media, a workflow to improve quality has become a prevalent component in the pipeline for many projects. Capturing this data has become easier than ever but processing it for noise reduction, clipping, and other quality issues can be important for creating the best experience.

We'll discuss a recent project to explore audio data and what it means to be an insightful judge of quality. Using python staples such as Matplotlib we explore how to visualize audio data, and how visualizing can help give us insights into the world of podcasts and by extension content production.

Learn more: https://go.dolby.io/pydata-2021