Gpu Based Transcriptions Meeting Minutes

D 56 completed
Cli Tool
unknown / python · tiny
21
Files
2,090
LOC
0
Frameworks
3
Languages

Pipeline State

completed
Run ID
#355600
Phase
done
Progress
1%
Started
Finished
2026-04-13 01:31:02
LLM tokens
0

Pipeline Metadata

Stage
Skipped
Decision
skip_scaffold_dup
Novelty
27.17
Framework unique
Isolation
Last stage change
2026-04-16 18:15:42
Deduplication group #47591
Member of a group with 1 similar repo(s) — canonical #65621 view group →
Top concepts (1)
Data/ML
Source: Repobility analyzer · https://repobility.com

AI Prompt

Build me a comprehensive toolkit in Python for processing long audio recordings. I need it to handle GPU-accelerated transcription using faster-whisper, ideally processing audio at high speed. The system should also detect the language and route the transcription to the best model. After transcription, I want to generate structured meeting minutes, detect speaker emotions using Wav2Vec2, and enrich the final output with AI insights like summaries and intent using Claude. Please include functionality for multi-language support and provide examples for running the full pipeline.
python gpu audio-processing transcription meeting-minutes pytorch cuda ai nlp
Generated by gemma4:latest

Catalog Information

A toolkit that transcribes long audio recordings using GPU acceleration, generates structured meeting minutes, detects language and speaker emotions, and enriches transcripts with AI insights.

Description

This toolkit provides a comprehensive solution for converting lengthy audio recordings into accurate transcripts using GPU acceleration, enabling rapid processing of multi‑hour files in seconds. It automatically detects language and routes the audio to the most suitable model, supporting over 90 languages via Whisper. The toolkit also performs voice emotion analysis to identify states such as anger, happiness, and sadness, offering deeper insight into meeting dynamics. AI enrichment modules extract summaries, intents, and entities from the transcripts, delivering actionable information. The entire workflow is accessible through a simple command‑line interface with ready‑made examples for real‑world meeting processing.

الوصف

يُقدّم هذا الأداة حلاً متكاملاً لتحويل التسجيلات الصوتية الطويلة إلى نصوص دقيقة باستخدام تسريع GPU، مما يتيح معالجة ملفات تمتد لعدة ساعات في ثوانٍ معدودة. تتضمن الأداة ميزة اكتشاف اللغة تلقائياً وتوجيهها إلى النموذج الأمثل، مع دعم أكثر من 90 لغة عبر Whisper. كما توفر تحليل المشاعر الصوتية لتحديد حالات الغضب والفرح والحزن، ما يساعد في فهم ديناميكيات الاجتماع. بالإضافة إلى ذلك، تُضيف الأداة ملخصات، نوايا، ومصطلحات مُستخرجة باستخدام نماذج AI المتقدمة. تُدمج هذه المميزات في واجهة سطر أوامر سهلة الاستخدام، مع أمثلة عملية لمعالجة اجتماعات طويلة. تُعد الأداة خياراً مثالياً للفرق التي تحتاج إلى استخراج رؤى فورية من محاضر الاجتماعات دون انتظار طويلة.

Novelty

8/10

Tags

audio-transcription meeting-minutes-generation multilingual-support emotion-detection gpu-acceleration ai-enrichment voice-analysis

Technologies

huggingface numpy pytorch rich

Claude Models

claude-opus-4.6

Quality Score

D
55.8/100
Structure
49
Code Quality
75
Documentation
65
Testing
0
Practices
55
Security
92
Dependencies
60

Strengths

  • Consistent naming conventions (snake_case)
  • Good security practices \u2014 no major issues detected
  • Properly licensed project

Weaknesses

  • No tests found \u2014 high risk of regressions
  • No CI/CD configuration \u2014 manual testing and deployment

Recommendations

  • Add a test suite \u2014 start with critical path integration tests
  • Set up CI/CD (GitHub Actions recommended) to automate testing and deployment
  • Add a linter configuration to enforce code style consistency

Security & Health

4.1h
Tech Debt (D)
A
OWASP (100%)
PASS
Quality Gate
A
Risk (5)
Repobility (the analyzer behind this table) · https://repobility.com
MIT
License
8.8%
Duplication
Full Security Report AI Fix Prompts SARIF SBOM

Languages

python
89.2%
markdown
9.5%
text
1.2%

Frameworks

None detected

Concepts (1)

Open data · scored by Repobility · https://repobility.com
CategoryNameDescriptionConfidence
Open data scored by Repobility · https://repobility.com
auto_categoryData/MLdata-ml60%

Quality Timeline

1 quality score recorded.

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