REPOGEO REPORT · LITE

ABexit/ASR-LLM-TTS

Default branch master · commit e94be138 · scanned 5/21/2026, 5:58:45 PM

GitHub: 1,193 stars · 195 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)

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

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 ABexit/ASR-LLM-TTS, 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

hightopics#1

Add relevant topics to improve discoverability

Why:

COPY-PASTE FIX

asr, llm, tts, speech-interaction, conversational-ai, open-source-ai, voice-assistant, speech-to-text, text-to-speech

highreadme#2

Add a concise project overview to the README

Why:

CURRENT

# 环境配置详细教程 B站

COPY-PASTE FIX

ABexit/ASR-LLM-TTS is an open-source, end-to-end speech interaction system that seamlessly integrates Automatic Speech Recognition (ASR), Large Language Models (LLM), and Text-to-Speech (TTS). It provides a unified framework for building conversational AI applications using models like SenseVoice, QWen2.5, CosyVoice, Edge-TTS, and pyttsx3.

# 环境配置详细教程 B站

mediumhomepage#3
Add a homepage URL to the repository
Why:
COPY-PASTE FIX
```
[Insert URL to a live demo, project page, or relevant documentation here]
```

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 ABexit/ASR-LLM-TTS

Avg rank

—

Lower is better. #1 = top recommendation.

Share of voice

Of all named tools, what % are you?

Top rival

openai/whisper

Recommended in 1 of 2 queries

COMPETITOR LEADERBOARD

openai/whisper · recommended 1×
espnet/espnet · recommended 1×
Mozilla Common Voice TTS · recommended 1×
coqui-ai/TTS · recommended 1×
huggingface/transformers · recommended 1×

CATEGORY QUERY
How can I build an end-to-end speech AI system with open-source models?
you: not recommended
AI recommended (in order):
1. Whisper (openai/whisper)
2. ESPnet (espnet/espnet)
3. Mozilla Common Voice TTS
4. Coqui TTS (coqui-ai/TTS)
5. Hugging Face Transformers (huggingface/transformers)
6. Wav2Vec2
7. HuBERT
8. Bark
9. Valle
10. YourTTS
11. Kaldi (kaldi-asr/kaldi)
12. Merlin
13. Tacotron 2
14. SpeechBrain (speechbrain/speechbrain)
15. Rhasspy (rhasspy/rhasspy)
16. Mycroft Mimic 3 (MycroftAI/mimic3)
AI recommended 16 alternatives but never named ABexit/ASR-LLM-TTS. This is the gap to close.
Show full AI answer
CATEGORY QUERY
What tools integrate automatic speech recognition, language models, and text-to-speech?
you: not recommended
AI recommended (in order):
1. Google Cloud AI Platform
2. Google Cloud Speech-to-Text
3. Google Cloud Text-to-Speech
4. Google Cloud Vertex AI
5. Azure AI Services
6. Azure Speech-to-Text
7. Azure Text-to-Speech
8. Azure OpenAI Service
9. AWS AI Services
10. Amazon Transcribe
11. Amazon Polly
12. Amazon Comprehend
13. Amazon Bedrock
14. OpenAI API
15. Whisper
16. ElevenLabs
17. Hugging Face Transformers (https://github.com/huggingface/transformers)
18. Hugging Face Inference API
19. Deepgram
AI recommended 19 alternatives but never named ABexit/ASR-LLM-TTS. 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 ABexit/ASR-LLM-TTS?
pass
AI named ABexit/ASR-LLM-TTS explicitly
AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?
If a team adopts ABexit/ASR-LLM-TTS in production, what risks or prerequisites should they evaluate first?
pass
AI named ABexit/ASR-LLM-TTS 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 ABexit/ASR-LLM-TTS solve, and who is the primary audience?
pass
AI named ABexit/ASR-LLM-TTS explicitly
AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

Embed your GEO score

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MARKDOWN (README)

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ABexit/ASR-LLM-TTS — 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