RRepoGEO

REPOGEO REPORT · LITE

LinkSoul-AI/LLaSM

Default branch main · commit 3443b79c · scanned 6/1/2026, 1:49:05 AM

GitHub: 559 stars · 53 forks

AI VISIBILITY SCORE
35 /100
Critical
Category recall
0 / 2
Not recommended in any query
Rule findings
1 pass · 1 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 LinkSoul-AI/LLaSM, 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
    Clarify LLaSM's core differentiator in the README's opening statement

    Why:

    CURRENT
    开源，可商用的**中英文双语语音-语言助手 LLaSM 以及中英文语音 SFT 数据集 LLaSM-Audio-Instructions**，第一个支持中英文语音-文本多模态对话的开源可商用对话模型。
    COPY-PASTE FIX
    LLaSM 是第一个开源、可商用的中英文双语语音-文本多模态对话模型，它将语音输入直接集成到大型语言模型中，作为语音-语言助手，旨在大幅改善以文本为输入的大模型的使用体验，并避免了基于 ASR 解决方案的繁琐流程以及可能引入的错误。我们还提供了中英文语音 SFT 数据集 LLaSM-Audio-Instructions。
  • hightopics#2
    Add specific topics to improve categorization

    Why:

    COPY-PASTE FIX
    multimodal-ai, speech-to-text, large-language-models, conversational-ai, voice-assistant, bilingual, open-source, llm, speech-llm
  • mediumabout#3
    Refine the repository description for clarity and differentiation

    Why:

    CURRENT
    第一个支持中英文双语语音-文本多模态对话的开源可商用对话模型。便捷的语音输入将大幅改善以文本为输入的大模型的使用体验，同时避免了基于 ASR 解决方案的繁琐流程以及可能引入的错误。
    COPY-PASTE FIX
    LLaSM 是第一个开源、可商用的中英文双语语音-文本多模态对话模型，它将语音直接集成到大型语言模型中，作为语音-语言助手，旨在改善 LLM 体验并避免传统 ASR 方案的局限性。

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 LinkSoul-AI/LLaSM
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Google Cloud Speech-to-Text API
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. Google Cloud Speech-to-Text API · recommended 1×
  2. openai/whisper · recommended 1×
  3. AWS Amazon Transcribe · recommended 1×
  4. AssemblyAI · recommended 1×
  5. Microsoft Azure Cognitive Services Speech · recommended 1×
  • CATEGORY QUERY
    How to integrate direct voice input into a large language model for conversational use cases?
    you: not recommended
    AI recommended (in order):
    1. Google Cloud Speech-to-Text API
    2. OpenAI Whisper (openai/whisper)
    3. AWS Amazon Transcribe
    4. AssemblyAI
    5. Microsoft Azure Cognitive Services Speech
    6. Deepgram
    7. Mozilla DeepSpeech (mozilla/DeepSpeech)

    AI recommended 7 alternatives but never named LinkSoul-AI/LLaSM. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Looking for an open-source, commercially viable, bilingual speech-to-text model for AI assistants.
    you: not recommended
    AI recommended (in order):
    1. Whisper
    2. Mozilla DeepSpeech
    3. Wav2Vec 2.0
    4. ESPnet
    5. Kaldi

    AI recommended 5 alternatives but never named LinkSoul-AI/LLaSM. This is the gap to close.

    Show full AI answer

Objective checks

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

  • Metadata completeness
    warn

    Suggestion:

  • 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 LinkSoul-AI/LLaSM?
    pass
    AI named LinkSoul-AI/LLaSM explicitly

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

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

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

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  • Brand-free category queries5 vs 2 in Lite
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