Relativity App Hub
The App Hub includes integrations built by Relativity or our community. Find solutions that best suit your unique data challenges.
Description
Endorsed by NVIDIA's Founder, President & CEO, Voice Identification Management is available at all stages of the Electronic Discovery Reference Model from Identification & Collection through to Production & Presentation.
Solution Description
Voice Identification Management correctly attributes the same individual across multiple spoken languages and dialects and is robust for wide variations in audio quality.
Voice Identification Management is deployable prior to, alongside, or post Relativity processing.
Voice Identification Management provides a matrix of names linked to processed recordings in extracted metadata style for upload into Relativity or any downstream Trial Preparation platforms.
Review and analyse voice recordings as a single phase exercise, rather than moving back and forth across the case timeline as additional instances where a particular speaker is present on calls are identified by human review.
Review and analyse voice recordings as a single phase exercise, rather than moving back and forth across the case timeline as additional instances where a particular speaker is present on calls are identified by human review.
Where an unknown John or Jane Doe is encountered and the contents of the conversation mean any other recordings where they also feature might be of interest, that set of recordings can be rapidly determined and then reviewed.
Based on a CNN/RNN neural networking system with hierarchical clustering, and focusing on how a body generates sound, it is agnostic of languages and dialects spoken.
Intelligent Voice Identification Management can be deployed edge, data center, or private AWS or Azure, utilizing either CPU or GPU resources.
Reach out to us with any questions you may have or to discuss next steps.
Based on a CNN/RNN neural networking system with hierarchical clustering, and focusing on how a body generates sound, it is agnostic of languages and dialects spoken.
Intelligent Voice Identification Management can be deployed edge, data center, or private AWS or Azure, utilizing either CPU or GPU resources.
Reach out to us with any questions you may have or to discuss next steps.
Key Benefits
- Provides robust and defensible identification and collection for voice.
- Mitigates the quality or otherwise of information governance prior to the case.
- Mitigates the absence of a regulatory minimum for voice recording quality in many jurisdictions and domains.
- Review and analyse all recordings where a particular speaker features regardless of metadata attribution.
- Demonstrably performant even where reviewers, long familiar with accents in a particular locale and with the custodians themselves, struggle to distinguish between different people speaking.
- Mitigates the full spectrum of voice metadata issues including:
- Borrowed credentials for desk phone logins
- Out of date phone number registries
- Conference call speaker phones
- Withheld caller details
- Also applicable to deep fake videos and audio recordings.
- Available at all stages of the Electronic Discovery Reference Model from Identification & Collection through to Production & Presentation
