Speaker recognition – often referred to as speaker identification – engines in the Veritone cognitive engine ecosystem identify when speakers change and who those speakers are in a piece of audio.
Speaker recognition expands upon the capabilities of speaker detection engines by identifying the individual whose voice was detected in addition to specifying the points of time in the file in which the person started and stopped speaking.
Speaker Recognition Features:
- Trainable with Custom Libraries
Create custom models using unique voice identifiers and metadata with the Veritone Library application or your own to identify a custom set of speakers in audio files. Learn more.
- Near Real-Time Processing
Process audio and video files in near real-time for use cases requiring a quick speaker recognition turnaround.
- Files or Stream Support
Recognize speakers in short-form or long-form audio in audio and video recordings, streamed recordings, or live data streams.
- Flexible Deployment
Deploy in a new or integrate into an existing application in the cloud via aiWARE GraphQL APIs, or with a subset that can be deployed on-premise via a Docker container. Learn more.
- Powered by an AI Ecosystem
Leverage advanced speaker recognition machine learning algorithms from the Veritone managed cognitive engine ecosystem — including algorithms from Veritone, niche providers, and industry giants.