results in seconds.
Using biometric characteristics, ATIS’ Automatic Forensic Speaker Identification allows speakers to be analyzed and identified in a way that stands up in court. Our solution can process large amounts of data automatically, independent of the spoken language. This saves valuable investigation time and resources.
Import of recorded audio and video files
Learning process – creating a reference
Automated data structuring
Score assignment and narrowing down the number of suspects
Speakers are automatically recognized and categorized based on their voices. Even without knowing the speakers’ identities, the system can find their voices in other media recordings. The recognized speakers are identified in the media recordings.
Biometric Profile Database
The profile database can store a biometric voice print and other supplementary information about a person. These can then be matched against other media to identify a person.
Social Media Analysis
Social media content, such as YouTube videos, can be imported and matched against the profile database.
Speech-to-text technology automatically creates transcripts of the audio of a conversation.
Our web client-based solution runs in all common web browsers like Firefox or Chrome and does not require any additional installations or plugins.
Our solution has a user-friendly import function in which can process a wide range of audio and video files automatically.
Connection and Integration
Our solution can be used as an independent (stand-alone) system. It can also be connected to / integrated with existing or third-party systems via RESTful API.
Higher Detection Rates.
- Language-independent recognition of speakers
- Save time through efficient workflows
- Quickly and easily learn about any new activities of identified speakers
- Identify unknown speakers via automatic recognition in other recordings
- Take advantage of the many benefits of the Speech-to-Text feature
- Work more efficiently by categorizing recordings according to keywords
- Recognition of a known speaker in the recordings of the database
- Recognition of an unknown speaker by matching them against the database
- Search for specific conversation content using Speech-to-Text analysis