REPOGEO REPORT · LITE

coqui-ai/STT

Default branch main · commit a562b940 · scanned 6/24/2026, 12:52:14 PM

GitHub: 2,591 stars · 299 forks

Scan history for this repo

Score trend below includes all ready runs (older left, newer right; scroll horizontally if needed). The table is collapsed by default—expand for newest-first rows, 10 per page.

Score trend (left → right: older → newer)

3 ready scans. Expand the table below for newest-first rows (10 per page, paginated).

AI VISIBILITY SCORE

40 /100

Critical

Category recall

0 / 2

Not recommended in any query

Rule findings

2 pass · 0 warn · 0 fail

Objective metadata checks

AI knows your name

3 / 3

Direct prompts that named your repo

HOW TO READ THIS REPORT

Action plan is what to do next — copy-pasteable changes prioritized by impact. Category visibility is the real GEO test: when a user asks an AI a brand-free question that should surface coqui-ai/STT, does the AI actually recommend you — or your competitors? Objective checks verify the metadata signals AI engines weight first. Self-mention check detects whether AI even knows you exist by name.

Action plan — copy-paste fixes

3 prioritized changes generated by gemini-2.5-flash. Mark items done after you ship the fix.

OVERALL DIRECTION

highreadme#1

Rephrase README introduction to reflect legacy status and DeepSpeech lineage

Why:

CURRENT

**Coqui STT** (🐸STT) is a fast, open-source, multi-platform, deep-learning toolkit for training and deploying speech-to-text models. 🐸STT is battle tested in both production and research 🚀

COPY-PASTE FIX

**Coqui STT** (🐸STT), formerly Mozilla DeepSpeech, was a fast, open-source, multi-platform, deep-learning toolkit for training and deploying speech-to-text models. While no longer actively maintained, it served as a battle-tested solution in both production and research.

mediumtopics#2

Add topics reflecting the project's legacy and unmaintained status

Why:

CURRENT

asr, automatic-speech-recognition, deep-learning, speech-recognition, speech-recognition-api, speech-recognizer, speech-to-text, stt, tensorflow, voice-recognition

COPY-PASTE FIX

asr, automatic-speech-recognition, deep-learning, speech-recognition, speech-recognition-api, speech-recognizer, speech-to-text, stt, tensorflow, voice-recognition, legacy, archive, historical-project, mozilla-deepspeech-successor

lowreadme#3

Create a dedicated 'Alternatives and Successors' section in the README

Why:

COPY-PASTE FIX

## Alternatives and Successors

For actively maintained speech-to-text solutions, consider newer models such as OpenAI Whisper. Coqui AI has shifted its focus to Coqui TTS and Coqui Studio for text-to-speech and related services.

Category GEO backends resolved for this scan: google/gemini-2.5-flash, deepseek/deepseek-v4-flash

Category visibility — the real GEO test

Brand-free queries asked to google/gemini-2.5-flash. Did AI recommend you, or someone else?

Same questions for every model — switch tabs to compare answers and rankings.

Recall

0 / 2

0% of queries surface coqui-ai/STT

Avg rank

—

Lower is better. #1 = top recommendation.

Share of voice

Of all named tools, what % are you?

Top rival

Hugging Face Transformers

Recommended in 2 of 2 queries

COMPETITOR LEADERBOARD

Hugging Face Transformers · recommended 2×
Mozilla DeepSpeech · recommended 2×
ESPnet · recommended 1×
Kaldi · recommended 1×
TensorFlow ASR · recommended 1×

CATEGORY QUERY
What open-source deep learning toolkit can I use for speech-to-text conversion?
you: not recommended
AI recommended (in order):
1. Hugging Face Transformers
2. Mozilla DeepSpeech
3. ESPnet
4. Kaldi
5. TensorFlow ASR
AI recommended 5 alternatives but never named coqui-ai/STT. This is the gap to close.
Show full AI answer
CATEGORY QUERY
Looking for an easy way to train and deploy automatic speech recognition models.
you: not recommended
AI recommended (in order):
1. Hugging Face Transformers
2. ð¤ Datasets
3. Gradio
4. AssemblyAI
5. Google Cloud Speech-to-Text API
6. Mozilla DeepSpeech
7. Picovoice
8. Rhino Speech-to-Text
9. Cheetah Speech-to-Text
10. AWS Transcribe
AI recommended 10 alternatives but never named coqui-ai/STT. This is the gap to close.
Show full AI answer

Objective checks

Rule-based audits of metadata signals AI engines weight most.

Metadata completeness
pass
README presence
pass

Self-mention check

Does AI even know your repo exists when asked about it directly?

Compared to common alternatives in this category, what is the core differentiator of coqui-ai/STT?
pass
AI named coqui-ai/STT explicitly
AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?
If a team adopts coqui-ai/STT in production, what risks or prerequisites should they evaluate first?
pass
AI named coqui-ai/STT explicitly
AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?
In one sentence, what problem does the repo coqui-ai/STT solve, and who is the primary audience?
pass
AI named coqui-ai/STT explicitly
AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

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MARKDOWN (README)

[![RepoGEO](https://repogeo.com/badge/coqui-ai/STT.svg)](https://repogeo.com/en/r/coqui-ai/STT)

HTML

<a href="https://repogeo.com/en/r/coqui-ai/STT"><img src="https://repogeo.com/badge/coqui-ai/STT.svg" alt="RepoGEO" /></a>

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coqui-ai/STT — Lite scans stay free; this card itemizes Pro deep limits vs Lite.

Deep reports10 / month
Brand-free category queries5 vs 2 in Lite
Prioritized action items8 vs 3 in Lite