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Implementation of Speaker Diarization on Client Side.

Description

Implement speaker diarization functionality on the client side to identify and separate multiple speakers from audio recordings or live audio streams. The feature should provide speaker-wise segmentation and labeling in the user interface, improving conversation readability and analysis.

Objectives

  • Integrate client-side speaker diarization processing/workflow.
  • Detect speaker changes within uploaded or recorded audio.
  • Display speaker-separated transcripts in the frontend UI.
  • Ensure smooth interaction between frontend and backend diarization services/APIs.
  • Optimize performance for real-time or near real-time processing.

Scope of Work

  • Add audio input handling for uploaded and recorded files.
  • Implement API integration for diarization inference.
  • Parse and render speaker timestamps and labels on the client side.
  • Design responsive UI components for speaker-based transcript visualization.
  • Handle loading states, errors, and unsupported audio formats.
  • Ensure compatibility across major browsers and devices.

Expected Outcome

  • Users can upload or record audio and view transcripts grouped by identified speakers.
  • Speaker transitions are clearly visualized with timestamps and labels.
  • Improved usability and readability of multi-speaker conversations.

Technical Requirements

  • Frontend framework integration (React/Next.js or relevant stack).
  • REST/WebSocket API communication for diarization results.
  • Efficient state management for transcript updates.
  • Proper error handling and validation mechanisms.

Acceptance Criteria

  • Audio files are successfully processed for speaker diarization.
  • Multiple speakers are accurately separated and labeled in the UI.
  • Transcript rendering updates dynamically without UI issues.
  • Error and edge cases are handled gracefully.
  • Feature is tested and verified on supported environments.