THTutorHero

Everything / Voice and audio / Speech to text

Trend in Voice and audio · tag speech-to-text · through Sep 2026

Speech to text Accelerating

On TutorHero's Everything Index, Speech to text is accelerating on GitHub: 1.35 of every 10,000 new public repos over the last three months (1.3k a month), 5x vs a year ago. The 12-month forecast says rising (+70%). By the end of 2032, lines in the same state ended between 0.01x and 2.5x of where they started (median 0.54x).

Per 10k new repos1.351.3k new repos a month
Year over year5x3 months: +64%
Next 12 months+70%80% band +44% to 5x
2032, median of history0.54x90% of past cases: 0.01x to 2.5x
Attention2.28%of new stars, +83% in a year
Jev 2032 call1.84xTop quarter of similar lines
Share on X

Since 2019, and the range to 2032

0.030.10.3131020192020202120222023202420252026202720282029203020312032Range to 2032 (history of similar lines)Stable Diffusion releasedChatGPT launchesGPT-4Llama 2, open weightsModel Context ProtocolDeepSeek-R1Claude Code previewHigh 3.35Jev 2.49Median 0.73Low 0.01

New repos per 10,000 (3-month average, log scale)12-month forecastRange to 2032: middle half and 90% of past similar linesJev's 2032 call

The range is not a forecast of this line: it is what GitHub lines in the same state (more than doubled its share of new repos in a year) did 1 to 5 years later, 2019 to 2026, applied to today's level. Past 5 years it is stretched, not measured. Checked out of time (learned before 2022, scored after), 71% of outcomes landed inside the 90% range, so read it as wide. Open it in the Everything chart.

Week by week

Last week558 new reposOct 12 to Oct 18 · -8% against the field
Last 4 weeks• +0%1.7k new repos, against the 4 weeks before and the field
AprMayJunJulAugSepOct

New public repos with the speech-to-text tag each week (Monday to Sunday, UTC). The outlined bars, last week included, are still filling in, as tags are often added days after a repo is created, so their height will grow a little. "Against the field" divides the change by what the typical tag did, so a wave that lifts every tag does not count. Hover for the numbers.

Built vs talked about

Hacker News3 stories a month-18% share of HN vs a year ago · titles with "speech-to-text"

Each line is its own share (of all new GitHub repos, all Hacker News stories, all English Wikipedia views, all new stars on the repos we track), shown as a share of its own peak, so the timing and shape compare even though the units differ. Hover for the counts. Tap a name to hide or show a line.

What it means

Studentslearning it, contributing, getting hiredTop priority
  • Worth learning now: Speech to text is accelerating, 5x share of new GitHub repos vs a year ago.
  • Start by reading debpalash/VoiceStudio (+37.5k stars in 3 months) and OpenWhispr/openwhispr (+3.0k stars in 3 months).
  • People to follow: ggml, SYSTRAN, Max Bain.
  • Jev for someone who wants to contribute or get hired: Top priority (3.6 of 4).
Founders and builderswhat to build nextCommit this year
  • Builders and attention both rising: new repos 5x, attention +83% in a year.
  • 14.7 new stars per new repo over 3 months, vs 8.50 for the typical trend: more demand per project than most fields.
  • The 12-month forecast for its share: +70% (Rising).
  • Jev for a builder: Commit this year (3.5 of 4).
Investorswhich fields deserve research timeCommit this year
  • History: of past GitHub lines that more than doubled its share of new repos in a year, 61% had a smaller share 3 to 5 years later and 8% at least doubled.
  • Jev's 2032 call: top quarter of similar lines, which on the base rates means about 1.84x today's share by the end of 2032.
  • Attention: 2.28% of new stars on the repos we track, +83% in a year.
  • Hacker News: 3 stories a month, -18% share in a year.
  • Jev for an investor: Commit this year (3.4 of 4).
  • Not investment advice: this measures what people build on GitHub, not any company.
Developers choosing toolswhich tools to adoptCommit this year
  • Most-starred tools here lately: debpalash/VoiceStudio (vouched), OpenWhispr/openwhispr.
  • The field is accelerating, so expect new tools and fast changes; pin versions.
  • Jev for a developer picking tools: Commit this year (3.3 of 4).

Repos carrying it now

debpalash/VoiceStudioVoiceStudio is the open-source, fully-local ElevenLabs alternative — voice cloning, voice design, video dubbing, dictation, transcription & +37.5k stars in 3 months · vouched
OpenWhispr/openwhisprVoice-to-text dictation app with local (Nvidia Parakeet/Whisper) and cloud models (BYOK). Privacy-first and available cross-platform.+3.0k stars in 3 months
cjpais/HandyA free, open source, and extensible speech-to-text application that works completely offline.+1.9k stars in 3 months
Zackriya-Solutions/meetilyPrivacy first, AI meeting assistant with 4x faster Parakeet/Whisper live transcription, speaker diarization, and Ollama summarization built +1.4k stars in 3 months · organic
getopenscreen/openscreenRecord your screen, ship a demo. Free and open-source, GPU-accelerated, no watermarks, no subscriptions. Windows, macOS, Linux. Actively mai+1.2k stars in 3 months
Osmantic/ODSODS V3 Pre-Release: Public testing and refinement ahead of the official V3 launch. Turn your PC, Mac, or Linux box into a private AI server.+1.2k stars in 3 months · new

People building it

More in Voice and audio

Questions

Is Speech to text growing on GitHub?

Yes. Its share of all new public GitHub repos is 5x vs a year ago and +64% over the last three months (Sep 2026). Phase: Accelerating.

How many new Speech to text repos are created each month?

About 1.3k new public repos a month carry the speech-to-text tag (three-month average to Sep 2026), or 1.35 of every 10,000 new repos.

What will Speech to text look like in 2032?

Nobody knows, and we say how much. Of past GitHub lines that more than doubled its share of new repos in a year, the middle half had between 0.14x and 1.27x of their share 3 to 5 years later, and 61% ended smaller. Jev's call: Top quarter of similar lines.

Not investment advice. Measurements of what people build and star on GitHub, a statistical forecast, base rates and a model's reading of them. Nothing here is about any company's revenue, valuation or stock.