Transcription Pipeline: Bridging Analog & Digital

A scalable solution for researchers, journalists, authors, and archivists

Pipeline overview and value proposition below. Click button to view project example details.

Pipeline value proposition below.
Click the button for project example details.

Pipeline project example

The Challenge

Authors, Researchers, Genealogists, Archivists, and Journalists are Users who work consistently with audio media, handwritten notes, and scanned media, often across multiple platforms.

Existing tools like Otter.ai, Notion, Zapier, Zoom / Teams, Google Meetup and recorder each offer options for speech-to-text transcription, automation, or management of different source media.

Unfortunately, Users must pay for subscriptions to leverage these features fully.

Tool Shared functionality What's missing
Zapier Basic automation No deep data processing
Otter.ai Audio transcription No handwritten notes or custom outputs
Notion + API Manual organization No automation for merging sources
Tana (tana.inc) Note-taking + AI linking Not focused on audio/handwritten input
Readwise Aggregates highlights/notes No transcription or custom pipelines
Airtable Database for notes and data No native audio transcription, difficult extraction
Zoom / Teams Audio and meeting transcription, notes Manual extraction of transcription through copy/paste only. No capability to merge transcription and notes. No custom output.
Google Meet / Recorder Audio and meeting transcription, notes Audio transcription only through Recorder, No custom output.

Furthermore, none of these tools enable end-to-end transcription generation, management, and organization of source media from start to finish.

This is where my pipeline comes in.

What is the transcription pipeline? Current State

In its current state, the pipeline is a low-code, open-source automated transcription pipeline built with Python, PostgreSQL, and Bash, designed to convert audio files into structured, searchable text and metadata.

Currently, it operates as a backend-only tool accessible on GitHub, providing Developers, Researchers, and Technical Users with:

This demo walks through a demo of the transcription pipeline in its current state - assuming the User has either cloned or downloaded the repo assets from GitHub.

  • Speech-to-text transcription using Python + OpenAI Whisper in Python.

  • Metadata indexing (word count, keyword extraction, file size, timestamps).

  • Database integration for querying, analysis, and visualization in PostgreSQL/pgAdmin, SQLite, or may be customized for the db tool of preference.

  • Duplicate validation, exception tracking, and logging for robust data management.

  • Freedom to manage and organize source media across multiple platforms.

Let’s break it down

Who’s It For?

  • Transcribe and combine handwritten and audio recorded notes

  • Combine field notes, survey data, and audio recordings, into content with one unified source of truth.

  • Need to create lecture notes or student feedback loops

  • Want to document or organize meeting recordings, notes, handwritten brainstormed ideas

  • Need to curate handwritten, typed, and recorded source material across various platforms and applications

What Problem Does It Solve?

  • Manual transcription costs teams hours of rework

  • Speech-to-text and text-to-speech tools lack customization, searchability, and unified data management

  • No tool enables bulk processing, grouping by project, keyword extraction or metadata analysis in a single pipeline

  • Pipeline is and will remain platform agnostic, meaning Users may manage source media, transcriptions and metadata without API or manual extraction across multiple platforms

Value for Users

  • Automated transcription and metadata generation save hours of manual effort, freeing users to focus on analysis, creativity, and higher-value tasks.

  • Custom keywords and metadata make transcriptions fully searchable, enabling users to quickly locate, filter, and repurpose content across projects.

  • Eliminating manual processes reduces overhead, minimizes errors, and streamlines workflows—so teams can deliver results faster and with fewer resources.

  • The pipeline’s modular, backend-ready design allows users to build and organize large repositories of transcriptions and metadata.

    This creates a unified foundation for media management, adaptable to any platform, system, or custom taxonomy (e.g., labels, categories, or projects).

Project Evolution

Stay Updated!

In the process of dockerizing the pipeline to build an app accessible to every user that could benefit from streamlined media transcription and management.

Follow me on GitHub to dive into the code that powers it!

Let’s work together!

Interested in collaborating? Have a project I could help with?

I support IT/Engineering Agile, SAFe, and Scrum teams as a Scrum Master, Project Manager, or Agile Leader.

I’m also pursuing Security+ to move into System Administration. Contact me — I’d love to work with you.