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Unlocking Data Trapped in Audio & Video Files
Paul Murphy gave a presentation about unlocking data trapped in audio and video files. He discussed trends like the end of the Gutenberg era and humans communicating more through sound and images instead of just text. Current tools are better at manipulating text than audio and video. Transcription and annotation of audio/video files using artificial intelligence could help extract more data by providing context, but context is also its own type of data. The presentation recapped that trends, technology, and context are important factors and that automation of transcription and annotation is the goal, though the state of the art is improving. Paul then solicited any questions and mentioned his company is hiring.
Unlocking Data Trapped in Audio & Video Files
- 1. Unlocking Data Trapped in Audio& Video Files Paul Murphy paul@clarify.io @prmurphy
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- 7. Context • My accent •The way I look • Bio (maybe)
- 8. My Background (whyam I here?) Banking » Telephony » Analytics When things important, they’re oral Oral means no trace Except that that’s no longer true
- 9. Why am Iexcited? • It’s a hard problem • It has to be solved (trends!) • I founded a company to do that
- 10. Trends • End ofthe Gutenberg Pause • Humans communicate through sound & images • Text is an optimization • Text is dead • Massive amounts of data are now being stored in A/V files
- 11. Where are wetoday? • Lots of tools for manipulating text • Almost no tools for manipulating audio & video
- 12. Where are wetoday? • Lots of tools for manipulating text • Almost no tools for manipulating audio & video
- 13. How can wecompute on A/V? • Transcription • Annotation
- 14. Turks are great! •Human transcription (APIs) • Manual annotation
- 15. Can those beautomated? • Transcription • Annotation » ASR » Artificial vision Of course! (or I wouldn’t be here)
- 16. ASRs • AT&T • IBMWatson • Vocapia • Speechmatics • …
- 17. Vision • Clarifai • Orbeus •Image Vision Labs • Face++ • …
- 18. State of theArt • Last 4 slides
- 19. Context (input) • Telephonyvs. wideband • Conversation vs. voicemail • Music vs. speech • English vs. Spanish Better & better data
- 20. Context (output) • Gender? •Identity? • Relationship? • Emotion? • Location? Need audio. Transcripts & annotations aren’t enough.
- 21. Recap…why does contextmatter? • Context helps us extract more & better data • Context is data We compute on data
- 22. Recap…where are wetoday • Trends • Technology • Context
- 23. Recap…where are wetoday
- 24. Recap…where are wetoday
- 25. Recap…where are wetoday
- 26. Recap…where are wetoday
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- 28. Any Questions? PS. We’rehiring! Paul Murphy paul@clarify.io @prmurphy