RRepoGEO

REPOGEO REPORT · LITE

ictnlp/StreamSpeech

Default branch main · commit 220273fd · scanned 6/27/2026, 11:52:41 AM

GitHub: 1,274 stars · 104 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
64 /100
Needs work
Category recall
1 / 2
Avg rank #4.0 when recommended
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 ictnlp/StreamSpeech, 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
    Add a clear, concise positioning statement to the README's opening

    Why:

    COPY-PASTE FIX
    Insert the following sentence directly after the `# StreamSpeech` heading: 'StreamSpeech is an open-source, all-in-one seamless model designed for researchers and developers to build advanced offline and simultaneous speech recognition, translation, and synthesis systems.'
  • mediumabout#2
    Refine the GitHub repository description to emphasize 'open-source model'

    Why:

    CURRENT
    StreamSpeech is an “All in One” seamless model for offline and simultaneous speech recognition, speech translation and speech synthesis.
    COPY-PASTE FIX
    StreamSpeech is an open-source, all-in-one seamless model for building offline and simultaneous speech recognition, speech translation, and speech synthesis applications.
  • lowcomparison#3
    Add a 'Comparison' section to the README

    Why:

    COPY-PASTE FIX
    Add a new section titled `## Comparison with Other Models` that briefly outlines how StreamSpeech differentiates itself from similar open-source models such as SeamlessM4T, Translatotron 2, or OpenAI Whisper, focusing on its 'all-in-one' and simultaneous capabilities.

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
1 / 2
50% of queries surface ictnlp/StreamSpeech
Avg rank
#4.0
Lower is better. #1 = top recommendation.
Share of voice
3%
Of all named tools, what % are you?
Top rival
Google Cloud Translation API
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. Google Cloud Translation API · recommended 2×
  2. Translatotron 2 · recommended 1×
  3. SeamlessM4T · recommended 1×
  4. SeamlessExpressive · recommended 1×
  5. OpenAI Whisper · recommended 1×
  • CATEGORY QUERY
    What are the best models for simultaneous speech recognition, translation, and synthesis?
    you: #4
    AI recommended (in order):
    1. Translatotron 2
    2. SeamlessM4T
    3. SeamlessExpressive
    4. StreamSpeech ← you
    5. OpenAI Whisper
    6. Meta NLLB-200
    7. Microsoft VALL-E
    8. VALL-E-X
    9. Coqui XTTSv2
    10. Amazon Transcribe
    11. Amazon Translate
    12. Amazon Polly
    13. Google Cloud Speech-to-Text
    14. Google Cloud Translation API
    15. Google Cloud Text-to-Speech
    Show full AI answer
  • CATEGORY QUERY
    Seeking a unified streaming solution for real-time speech-to-speech translation with ASR output.
    you: not recommended
    AI recommended (in order):
    1. Google Cloud Speech-to-Text API
    2. Google Cloud Translation API
    3. Google Cloud Text-to-Speech API
    4. AWS Transcribe
    5. AWS Translate
    6. AWS Polly
    7. Microsoft Azure Speech Service
    8. Azure Speech-to-text
    9. Azure Translator
    10. Azure Text-to-speech
    11. DeepL API
    12. AssemblyAI
    13. ElevenLabs
    14. OpenAI Whisper (openai/whisper)
    15. Hugging Face Transformers (huggingface/transformers)

    AI recommended 15 alternatives but never named ictnlp/StreamSpeech. 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 ictnlp/StreamSpeech?
    pass
    AI named ictnlp/StreamSpeech explicitly

    AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

  • If a team adopts ictnlp/StreamSpeech in production, what risks or prerequisites should they evaluate first?
    pass
    AI named ictnlp/StreamSpeech 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 ictnlp/StreamSpeech solve, and who is the primary audience?
    pass
    AI named ictnlp/StreamSpeech explicitly

    AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

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ictnlp/StreamSpeech — 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