murtaza-nasir/speakr

Speakr is a personal, self-hosted web application designed for transcribing audio recordings

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Summary Information

Updated 31 minutes ago
Added to GitGenius on September 17th, 2026
Created on May 5th, 2025
Open Issues & Pull Requests: 6 (+0)
GitHub issues: Enabled
Number of forks: 331
Total Stargazers: 3,978 (+1)
Total Subscribers: 23 (+0)

Repository Insights (GitGenius)

Median issue/PR response: 2.4 days
Mean response time: 6.7 days
90th percentile: 19.8 days
Tracked items: 297

Most active contributors

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How this project is maintained

Practically every issue opened in the past year has drawn a reply. 97% of issues opened in the past year have since been closed. Three people close 87% of everything that gets resolved.

Charts & Analytics

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Issue Activity (beta)

Open issues: 6
New in 7 days: 1
Closed in 7 days: 4
Avg open age: 80 days
Stale 30+ days: 2
Stale 90+ days: 1

Recent activity

Opened in 7 days: 1
Closed in 7 days: 4
Comments in 7 days: 0
Events in 7 days: 0

Top labels

  • enhancement (1)

Detailed Description

Speakr is a self-hosted web application for transcribing audio recordings.

The tool addresses the need to convert audio files into text while maintaining privacy and control over your data. Rather than relying on cloud-based transcription services, Speakr runs on your own infrastructure, allowing you to process audio locally without sending recordings to external servers. The application handles the transcription workflow through a web interface, making it accessible without requiring command-line expertise.

Speakr suits individuals and organizations that prioritize data privacy or operate in environments where sending audio to third-party services is not feasible. It works well for personal projects, small teams, or deployments where you control the hardware and can manage the infrastructure yourself. The self-hosted nature means you avoid recurring subscription costs associated with commercial transcription APIs, though you assume responsibility for maintaining the server and managing computational resources.

The project shows active development with regular commits and ongoing refinement of its codebase. The maintainer responds to issues and incorporates feedback into the tool's evolution. The project maintains a focused scope on core transcription functionality rather than attempting to be a comprehensive audio processing suite.