Overview#
A recorded deposition runs two hours. A surveillance intercept spans several sessions across multiple days. A military debriefing produces hours of audio in two languages. In each case, the value of the recording depends on how quickly and accurately it can be turned into text that investigators and analysts can search, annotate, and cite. The Media Transcription Services module processes audio and video evidence through an AI-powered speech-to-text pipeline that identifies individual speakers, aligns every word to its position in the recording, and delivers a searchable, formatted transcript ready for case integration.
The module is built for law enforcement interview management, surveillance evidence processing, military operational debrief support, and court evidence preparation where transcript accuracy and speaker attribution are both critical.
Key Features#
- AI-powered speech-to-text transcription with high accuracy across diverse audio quality levels
- Speaker diarisation identifying and labelling individual speakers throughout the recording
- Timestamp alignment linking every transcript segment to its exact position in the source audio or video
- Multi-language transcription support for diverse evidence sources and operational contexts
- Automated punctuation and formatting for readability without manual editing
- Confidence scoring at word and segment level to flag uncertain passages for human review
- Custom vocabulary support for domain-specific terminology, codenames, and proper nouns
- Batch transcription processing for large audio and video collections
Use Cases#
- Transcribing recorded interviews and custody interactions with per-speaker labelling for case review and legal production
- Creating searchable transcripts from surveillance audio and intercepted communications for investigative analysis
- Processing multi-language evidence with accurate transcription and speaker labels, reducing the need for manual translation at the initial review stage
- Batch-transcribing large audio evidence collections so investigators can search content by keyword rather than reviewing recordings sequentially
- Supporting military debrief transcription with custom vocabulary for operational terminology and multi-language source material
Integration#
Media Transcription Services connects with evidence management, the audio analysis module, and search indexing systems. Completed transcripts are linked to their source media with timestamp anchors, stored with cryptographic integrity on Cloudflare R2, and made available for full-text search within the investigation platform.
Open Standards#
- ISO 639-1 (Language Codes): Language identification tags (e.g.
en,en-US) conforming to ISO 639-1 are used throughout the transcription pipeline for automatic language detection, multi-language transcript labelling, and routing to translation services when a non-English language is detected. - W3C WebVTT: The Cloudflare Workers AI Whisper integration returns timestamped transcript output in WebVTT format, enabling time-aligned caption and subtitle export that can be consumed by any W3C WebVTT-compliant player or review tool.
- FIPS 180-4 SHA-256: Every piece of audio/video evidence uploaded to the platform is integrity-stamped with a SHA-256 hash; the evidence management service also constructs a Merkle tree of SHA-256 hashes across evidence records to provide tamper-evident chain-of-custody for completed transcripts.
- W3C Verifiable Credentials (VC Data Model): Chain-of-custody transfers for transcribed evidence are issued and verified as W3C Verifiable Credentials, providing a cryptographically signed provenance trail suitable for court admissibility.
- IANA Media Types (MIME): Audio and video evidence is uploaded and fetched using standard IANA-registered MIME types (e.g.
audio/wav,audio/mp3,video/mp4) for content negotiation between the ingestion pipeline and transcription providers. - ITU-T G.711 / 16-bit Linear PCM: Raw audio buffers are processed as 16-bit signed PCM (the format used by G.711 µ-law telephony streams from Twilio at 8 kHz), enabling direct audio analysis and confidence scoring without an intermediate decode step.
- GraphQL (June 2018 Specification): Transcript retrieval, speaker-segment queries, confidence-score access, and case-file integration are all exposed via a GraphQL API, allowing clients to request precisely the transcript fields and metadata they require.
Last Reviewed: 2026-02-23 Last Updated: 2026-04-14