--- title: "stt vs LiveCaptions-Translator" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/jianchang512-stt-vs-sakirinn-livecaptions-translator" tools: ["jianchang512-stt", "sakirinn-livecaptions-translator"] --- # stt vs LiveCaptions-Translator *GraphCanon updated Jul 30, 2026* ## Verdict Pick stt if stt is a Python-based local offline speech-to-text tool that uses fast-whipser for converting audio from video and audio files into text, including JSON, SRT subtitles, or plain text formats; pick LiveCaptions-Translator if liveCaptions-Translator is ideal for Windows users seeking direct integration with Windows LiveCaptions for real-time audio-to-text translation. [stt](https://pyvideotrans.com) reports 4.7k GitHub stars, 493 forks, and 100 open issues, last pushed Jan 22, 2026. [LiveCaptions-Translator](https://github.com/SakiRinn/LiveCaptions-Translator) has 3.4k stars, 240 forks, and 17 open issues, last pushed Jul 22, 2026. Figures are from public GitHub metadata via [stt's repository](https://github.com/jianchang512/stt) and [LiveCaptions-Translator's repository](https://github.com/SakiRinn/LiveCaptions-Translator). | | [stt](/tools/jianchang512-stt.md) | [LiveCaptions-Translator](/tools/sakirinn-livecaptions-translator.md) | | --- | --- | --- | | Tagline | A local offline speech-to-text tool for video and audio files. | Lightweight and powerful real-time audio/speech translation tool | | Stars | 4,712 | 3,415 | | Forks | 493 | 240 | | Open issues | 100 | 17 | | Language | Python | C# | | Adopt for | stt is a Python-based local offline speech-to-text tool that uses fast-whipser for converting audio from video and audio files into text, including JSON, SRT subtitles, or plain text formats. | LiveCaptions-Translator is ideal for Windows users seeking direct integration with Windows LiveCaptions for real-time audio-to-text translation. | | Persona | - | - | | Runtime | - | - | | License | GPL-3.0 | Apache-2.0 | | Categories | Speech & Audio | Speech & Audio | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [stt](/tools/jianchang512-stt.md) | [LiveCaptions-Translator](/tools/sakirinn-livecaptions-translator.md) | | --- | --- | --- | | Maintenance | Slowing (36%) | Active (82%) | | Days since push | 189d | 7d | | Open issues (now) | 100 | 17 | | Full report | [trust report](/tools/jianchang512-stt/trust.md) | [trust report](/tools/sakirinn-livecaptions-translator/trust.md) | ## Decision facts: stt - **Adopt for:** stt is a Python-based local offline speech-to-text tool that uses fast-whipser for converting audio from video and audio files into text, including JSON, SRT subtitles, or plain text formats. ## Decision facts: LiveCaptions-Translator - **Adopt for:** LiveCaptions-Translator is ideal for Windows users seeking direct integration with Windows LiveCaptions for real-time audio-to-text translation. ## Choose when ### Choose stt if… - stt is primarily Python; LiveCaptions-Translator is C#. - License: stt is GPL-3.0, LiveCaptions-Translator is Apache-2.0. - Tags unique to stt: audio-processing, fast-whisper, local-processing, offline. - Use stt if you require an offline, locally-run solution where internet dependence is not acceptable. ### Choose LiveCaptions-Translator if… - LiveCaptions-Translator is primarily C#; stt is Python. - License: LiveCaptions-Translator is Apache-2.0, stt is GPL-3.0. - Tags unique to LiveCaptions-Translator: api, api integration, audio-to-text, real-time. - You need an integrated solution operating directly on the Windows platform leveraging Windows LiveCaptions technology ## When NOT to use stt - Avoid using stt if your application relies on continuous updates and service improvements that are only available via web services. - Do not use stt in environments where CUDA acceleration cannot be supported, as it will limit processing speed without the GPU acceleration advantage. ## When NOT to use LiveCaptions-Translator - Your application runs exclusively on non-Windows platforms like MacOS or Linux - The scenario demands highly specialized linguistic capabilities not covered by the general-purpose translations offered here ## Common questions ### What is the difference between stt and LiveCaptions-Translator? stt: A local offline speech-to-text tool for video and audio files.. LiveCaptions-Translator: Lightweight and powerful real-time audio/speech translation tool. See the comparison table for live GitHub stats and shared categories. ### When should I choose stt over LiveCaptions-Translator? Choose stt over LiveCaptions-Translator when stt is primarily Python; LiveCaptions-Translator is C#; License: stt is GPL-3.0, LiveCaptions-Translator is Apache-2.0; Tags unique to stt: audio-processing, fast-whisper, local-processing, offline; Use stt if you require an offline, locally-run solution where internet dependence is not acceptable. ### When should I choose LiveCaptions-Translator over stt? Choose LiveCaptions-Translator over stt when LiveCaptions-Translator is primarily C#; stt is Python; License: LiveCaptions-Translator is Apache-2.0, stt is GPL-3.0; Tags unique to LiveCaptions-Translator: api, api integration, audio-to-text, real-time; You need an integrated solution operating directly on the Windows platform leveraging Windows LiveCaptions technology. ### When should I avoid stt? Avoid using stt if your application relies on continuous updates and service improvements that are only available via web services. Do not use stt in environments where CUDA acceleration cannot be supported, as it will limit processing speed without the GPU acceleration advantage. ### When should I avoid LiveCaptions-Translator? Your application runs exclusively on non-Windows platforms like MacOS or Linux The scenario demands highly specialized linguistic capabilities not covered by the general-purpose translations offered here ### Is stt or LiveCaptions-Translator more popular on GitHub? stt has more GitHub stars (4,712 vs 3,415). Stars measure visibility, not whether either tool fits your constraints. ### Are stt and LiveCaptions-Translator open source? Yes - both are open-source projects on GitHub (stt: GPL-3.0, LiveCaptions-Translator: Apache-2.0). ### Where can I find alternatives to stt or LiveCaptions-Translator? GraphCanon lists graph-backed alternatives at [stt alternatives](/tools/jianchang512-stt/alternatives) and [LiveCaptions-Translator alternatives](/tools/sakirinn-livecaptions-translator/alternatives) ([stt markdown twin](/tools/jianchang512-stt/alternatives.md), [LiveCaptions-Translator markdown twin](/tools/sakirinn-livecaptions-translator/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/jianchang512-stt-vs-sakirinn-livecaptions-translator.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, stt or LiveCaptions-Translator? stt: Slowing. LiveCaptions-Translator: 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 stt and LiveCaptions-Translator? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [stt trust report](/tools/jianchang512-stt/trust); [LiveCaptions-Translator trust report](/tools/sakirinn-livecaptions-translator/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=jianchang512-stt`](/api/graphcanon/graph?tool=jianchang512-stt) - 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/_