Automated AI Workflow for Audio Video Evidence Review

Automated Evidence Review for Audio/Video Files

1. Initial Upload of Audio/Video Files

1.1 File Submission

Legal teams submit audio and video files through a secure online portal.

1.2 File Format Verification

The system checks for acceptable file formats (e.g., MP3, MP4, WAV) and notifies users of any issues.

2. AI Transcription Process

2.1 AI Transcription Tool Selection

Choose an AI-driven transcription tool such as:

• Otter.ai: Provides real-time transcription and collaboration features.
• Sonix: Offers automated transcription with multi-language support.
• Trint: Combines transcription with editing capabilities for accuracy.

2.2 Transcription Execution

The selected AI tool processes the audio/video files, converting speech to text.

2.3 Quality Assurance

AI algorithms analyze the transcription for accuracy, flagging any potential errors or unclear segments for human review.

3. Evidence Categorization

3.1 Content Analysis

Utilize AI-driven content analysis tools such as:

• IBM Watson: For sentiment analysis and keyword extraction.
• Google Cloud Natural Language: For entity recognition and topic classification.

3.2 Evidence Tagging

Automatically tag transcribed content based on identified keywords and themes relevant to the case.

4. Review and Approval

4.1 Human Review

Legal professionals review flagged segments and overall transcription for accuracy and relevance.

4.2 Approval Workflow

Once reviewed, the legal team provides approval or requests further revisions. This can be managed through tools like:

• Asana: For task management and tracking review progress.
• Trello: For visual project management of the review process.

5. Finalization and Reporting

5.1 Document Generation

Create a final report that includes the transcribed content, analysis results, and any annotations from the review process.

5.2 Archival of Evidence

Store the final report and original files in a secure digital repository for future reference.

6. Continuous Improvement

6.1 Feedback Loop

Gather feedback from legal teams regarding the transcription accuracy and workflow efficiency.

6.2 AI Model Training

Use feedback to refine AI models, improving future transcription accuracy and categorization.