Separate and Label Speakers Within Audio and Video Evidence 

Segment and organize spoken content in audio and video evidence by separating speakers and assigning generic labels within transcriptions, supporting structured review without identifying or verifying speaker identity. 

Separate and Label Speakers Within Audio and Video Evidence
AI-Powered Review-1

Speaker Segmentation

Segment audio within recordings based on distinct voice characteristics to distinguish between different speakers present in the evidence.

Speaker Labeling

Speaker Labeling

Apply neutral, system-generated speaker references within transcriptions to distinguish dialogue segments without assigning names or identities.

Transcript Alignment

Transcript Alignment

Align each transcribed segment with its corresponding speaker label, enabling reviewers to understand which portions of dialogue belong to each speaker.

Translate or transcribe recordings in 40+ languages

Multilingual Segmentation

Separate speakers based on voice segments rather than spoken language, allowing diarization to function across multilingual audio and video recordings.

Bring Structure to Multi-Speaker Evidence Review

Structured Transcript Review  

Speaker-labeled transcriptions organize multi-speaker dialogue into clearly defined segments, allowing investigators and reviewers to follow conversations methodically during evidence examination without inferring speaker identity. 

Structured Transcript Review

Improved Contextual Understanding 

Separating dialogue by speaker preserves conversational flow within transcriptions, helping reviewers distinguish individual statements and exchanges when analyzing recordings involving multiple participants. 

Improved Contextual Understanding

Consistent Analysis Across Languages 

Language-agnostic segmentation ensures speaker separation is applied consistently across audio and video evidence, including recordings that contain different or mixed spoken languages. 

Consistent Analysis Across Languages

Integrated Evidence Analysis Workflow 

Executing speaker diarization as part of transcription processing keeps speaker segmentation embedded within the evidence analysis workflow, eliminating the need for separate tools or post-processing steps. 

Integrated Evidence Analysis Workflow

Enable Speaker-Segmented Transcription Review

The Intelligent Path from Evidence to Resolution

Collect

Collect

Get evidence into your system. Upload files from any device or pull them in automatically from connected sources like bodycams or cloud storage.

Store-2

Store

Keep all your evidence in one secure, central location. Organize it by case and control who can access it, with protection for sensitive information.

Review & Process

Review & Process

Work with your evidence. Use tools to search, analyze, annotate, and redact videos and documents right within the platform with your team.

Share & Preserve

Share & Preserve

Close the loop. Share finalized evidence securely with prosecutors or other agencies or archive it to meet long-term legal requirements.

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