How to Review Audio Files Using eDiscovery AI
How to Review Audio Files Using eDiscovery AI
eDiscovery AI makes it easy to summarize and classify audio
content just as efficiently as text-based documents. This guide will walk you
through the process of reviewing audio files using our AI-powered system.
1. Getting
Started
Send
Documents to eDiscovery AI: Begin by using the Relativity Mass
action, Send to eDiscovery AI from Relativity.
Enter
your Prompts: Specify one or more detailed prompts describing the
issues to be identified during document review, the same way you would
for text-based documents.
2. Reviewing
Audio Content
Native
Audio Review: eDiscovery AI will review the native audio file and
analyze it based on the prompts entered by the user. This is not a review
of a transcript but rather a full native audio review of each file. Current
audio file types supported are: mp4, mp3, wav, mov, ogg, opus, wave, pcm,
vorbis, aac, mp2.
Sentiment
Analysis: eDiscovery AI is capable of understanding sentiment and
tone within audio files allowing you to identify instances where a
customer from a call center is upset, or where a meeting attendee was
speaking in a hostile tone to a coworker.
Audio
Clarity: eDiscovery AI can effectively review audio files even if
there is significant background noise or speakers have strong accents
even though human reviewers tend to struggle with this type of review.
3. Audio
Review Output
eDiscovery
AI Summary: For every audio file, you’ll get a succinct summary of
the entire file including the primary subject matter of the file.
Classification:
eDiscovery AI will review the audio files based on the criteria described
in your prompts and will classify each file for relevance based on that
criteria, just like with text based documents.
Explanation:
Every classification will also include an explanation describing why the
file was classified as relevant or not relevant to help provide clarity
and expedite any QC review.
Remember,
with eDiscovery AI, you can efficiently process, understand, and analyze audio
content, turning hours of recordings into searchable, classified data that
integrates seamlessly with your text-based eDiscovery process.
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