--- title: "dsnote vs awesome-whisper" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/mkiol-dsnote-vs-sindresorhus-awesome-whisper" tools: ["mkiol-dsnote", "sindresorhus-awesome-whisper"] --- # dsnote vs awesome-whisper *GraphCanon updated Sep 20, 2026* ## Verdict Pick dsnote if dsnote is an offline speech-to-text and text-to-speech Linux app for note-taking, reading, and translating developed in C++ with open-source libraries under various licenses like MPL-2.0; pick awesome-whisper if awesome-whisper is an organized repository aggregating resources for OpenAI's Whisper AI-powered speech recognition system, covering models, apps, bindings, packages, and community tools. [dsnote](https://github.com/mkiol/dsnote) reports 1.7k GitHub stars, 73 forks, and 147 open issues, last pushed Sep 19, 2026. [awesome-whisper](https://github.com/sindresorhus/awesome-whisper) has 2.4k stars, 180 forks, and 7 open issues, last pushed Sep 17, 2026. Figures are from public GitHub metadata via [dsnote's repository](https://github.com/mkiol/dsnote) and [awesome-whisper's repository](https://github.com/sindresorhus/awesome-whisper). | | [dsnote](/tools/mkiol-dsnote.md) | [awesome-whisper](/tools/sindresorhus-awesome-whisper.md) | | --- | --- | --- | | Tagline | An offline speech-to-text and text-to-speech Linux app for note taking, reading and translating. | Curated resources for Whisper speech recognition system | | Stars | 1,661 | 2,386 | | Forks | 73 | 180 | | Open issues | 147 | 7 | | Language | C++ | - | | Adopt for | dsnote is an offline speech-to-text and text-to-speech Linux app for note-taking, reading, and translating developed in C++ with open-source libraries under various licenses like MPL-2.0. | awesome-whisper is an organized repository aggregating resources for OpenAI's Whisper AI-powered speech recognition system, covering models, apps, bindings, packages, and community tools. | | Persona | - | - | | Runtime | - | - | | License | dsnote uses MPL-2.0, allowing redistribution, modification, and use in proprietary software with attribution but requires that derivative works are under the same license. | CC0-1.0 | | Categories | Speech & Audio | Speech & Audio | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [dsnote](/tools/mkiol-dsnote.md) | [awesome-whisper](/tools/sindresorhus-awesome-whisper.md) | | --- | --- | --- | | Days since push | 0d | 3d | | Open issues (now) | 147 | 7 | | Stars delta | +108 (30d) | +25 (30d) | | Open issues delta | +6 (30d) | 0 (30d) | | Full report | [trust report](/tools/mkiol-dsnote/trust.md) | [trust report](/tools/sindresorhus-awesome-whisper/trust.md) | ## Decision facts: dsnote - **Requirements:** - Requires C++ environment setup for building from source code, including dependencies such as autoconf, automake, boost-devel, cmake, and others.; - Must be installed in a Linux desktop environment. Install through Flatpak or build from source. - **Adopt for:** dsnote is an offline speech-to-text and text-to-speech Linux app for note-taking, reading, and translating developed in C++ with open-source libraries under various licenses like MPL-2.0. - **License detail:** dsnote uses MPL-2.0, allowing redistribution, modification, and use in proprietary software with attribution but requires that derivative works are under the same license. ## Decision facts: awesome-whisper - **Adopt for:** awesome-whisper is an organized repository aggregating resources for OpenAI's Whisper AI-powered speech recognition system, covering models, apps, bindings, packages, and community tools. ## Choose when ### Choose dsnote if… - License: dsnote is MPL-2.0, awesome-whisper is CC0-1.0. - Requirements: - Requires C++ environment setup for building from source code, including dependencies such as autoconf, automake, boost-devel, cmake, and others.; - Must be installed in a Linux desktop environment. Install through Flatpak or build from source.. - Tags unique to dsnote: asr, machine-translation, nmt, offline. - - For users who prefer working without internet access while needing speech recognition and machine translation capabilities. ### Choose awesome-whisper if… - License: awesome-whisper is CC0-1.0, dsnote is MPL-2.0. - Tags unique to awesome-whisper: ai, artificial-intelligence, gpt, openai. - When seeking curated information on Whisper variants optimized for various platforms and languages ## When NOT to use dsnote - - If the user's primary requirement is cloud-based services with real-time updates or extensive language databases not included in dsnote. - - For users who need a cross-platform solution since dsnote specifically supports Linux desktop environments and not Windows or Mac OS by default. ## When NOT to use awesome-whisper - If looking for resources related to speech recognition systems from other providers not listed under OpenAI's Whisper ecosystem - In cases where the focus is on using pre-integrated solutions without the need for model customization ## Common questions ### What is the difference between dsnote and awesome-whisper? dsnote: An offline speech-to-text and text-to-speech Linux app for note taking, reading and translating.. awesome-whisper: Curated resources for Whisper speech recognition system. See the comparison table for live GitHub stats and shared categories. ### When should I choose dsnote over awesome-whisper? Choose dsnote over awesome-whisper when License: dsnote is MPL-2.0, awesome-whisper is CC0-1.0; Requirements: - Requires C++ environment setup for building from source code, including dependencies such as autoconf, automake, boost-devel, cmake, and others.; - Must be installed in a Linux desktop environment. Install through Flatpak or build from source.; Tags unique to dsnote: asr, machine-translation, nmt, offline; - For users who prefer working without internet access while needing speech recognition and machine translation capabilities. ### When should I choose awesome-whisper over dsnote? Choose awesome-whisper over dsnote when License: awesome-whisper is CC0-1.0, dsnote is MPL-2.0; Tags unique to awesome-whisper: ai, artificial-intelligence, gpt, openai; When seeking curated information on Whisper variants optimized for various platforms and languages. ### When should I avoid dsnote? - If the user's primary requirement is cloud-based services with real-time updates or extensive language databases not included in dsnote. - For users who need a cross-platform solution since dsnote specifically supports Linux desktop environments and not Windows or Mac OS by default. ### When should I avoid awesome-whisper? If looking for resources related to speech recognition systems from other providers not listed under OpenAI's Whisper ecosystem In cases where the focus is on using pre-integrated solutions without the need for model customization ### Is dsnote or awesome-whisper more popular on GitHub? awesome-whisper has more GitHub stars (2,386 vs 1,661). Stars measure visibility, not whether either tool fits your constraints. ### Are dsnote and awesome-whisper open source? Yes - both are open-source projects on GitHub (dsnote: MPL-2.0, awesome-whisper: CC0-1.0). ### Where can I find alternatives to dsnote or awesome-whisper? GraphCanon lists graph-backed alternatives at [dsnote alternatives](/tools/mkiol-dsnote/alternatives) and [awesome-whisper alternatives](/tools/sindresorhus-awesome-whisper/alternatives) ([dsnote markdown twin](/tools/mkiol-dsnote/alternatives.md), [awesome-whisper markdown twin](/tools/sindresorhus-awesome-whisper/alternatives.md)), ranked by typed relationship edges rather than popularity votes. ### Is there a machine-readable version of this comparison? Yes. The markdown twin at [this comparison](/compare/mkiol-dsnote-vs-sindresorhus-awesome-whisper.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, dsnote or awesome-whisper? dsnote: Very active. awesome-whisper: Very active. Compare maintenance labels, days since push, and release cadence in the trust section below - stars alone do not measure maintenance. ### Where are the full trust reports for dsnote and awesome-whisper? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [dsnote trust report](/tools/mkiol-dsnote/trust); [awesome-whisper trust report](/tools/sindresorhus-awesome-whisper/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=mkiol-dsnote`](/api/graphcanon/graph?tool=mkiol-dsnote) - LLM index: [/llms.txt](/llms.txt) - Full corpus: [/llms-full.txt](/llms-full.txt) _GraphCanon - The knowledge graph for AI development. https://www.graphcanon.com/_