BabylPhysh Terminal - Professional Manual v0.8a3-Enterprise

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BABYLPHYSH TERMINAL

v0.8a3-Enterprise

Professional Subtitle Production Management System

System Overview

Current Release: v0.8a3-Enterprise
Status: Production Ready
Release Date: September 23, 2025
Architecture: Modular Python Package

BabylPhysh Terminal is a comprehensive subtitle production management system designed for professional documentary film workflows. It provides quality control, multi-language translation, batch processing, and intelligent file management capabilities.

Key Capabilities

Complete subtitle quality control and validation
Multi-language translation with 108+ language support
Intelligent language detection and file naming
Professional HTML/CSV reporting system
Frame rate detection and alignment
Batch processing and pipeline automation
Production analytics and insights

Terminal Interface

Interactive Command-Line Interface: BabylPhysh presents a simple menu-driven terminal interface for all operations.

Main Menu Display

╔══════════════════════════════════════════════════════════════════╗
║ 🎬 BABYLPHYSH TERMINAL v0.8a3-Enterprise ║
║ Professional Subtitle Production System ║
╚══════════════════════════════════════════════════════════════════╝

CORE PROCESSING MODES:
----------------------------------------------------------------------
1) QC-A	- Quality Check Analysis (No Changes)
2) QC-FX	- Quality Check & Fix
3) QC-DIFF	- Compare Original vs Processed
4) TRANS	- Translation
5) BT-QC	- Back-Translation Quality Check
6) CONFORM	- Language Conforming
7) SYNC	- Transcript Sync
8) SRT-NAME	- Batch Append Language Names

ENHANCED WORKFLOW MODES:
----------------------------------------------------------------------
9) BATCH-QC	- Batch Quality Control
P) PIPELINE	- Complete Production Workflow
A) ANALYSIS	- Enhanced Analysis Dashboard

----------------------------------------------------------------------
0) Exit
======================================================================
Enter number/letter or mode name (e.g., '1', 'P', or 'qc-a')

🎬 Select mode: _

Example User Session

$ python3 launch.py

Welcome to BabylPhysh Terminal Subtitle Toolkit!
Working directory: /Applications/BabylPhysh Terminal v0.8a3

[Menu displays as shown above]

🎬 Select mode: 4

=== TRANS: Translation ===

Available files:
1) [masters ]	documentary_episode1.en.sdh.srt
2) [masters ]	documentary_episode2.en.sdh.srt
3) [to_qc ]	movie_subtitle.en.srt

Choose file: 1

Selected: documentary_episode1.en.sdh.srt (245 subtitles)

🌍 Target Languages:
1)	Essential Pack (5 languages)
2)	Extended Pack (10 languages)
3)	Comprehensive Pack (20 languages)
4)	Custom selection

Select package [1]: 1

Processing: Spanish (Latin America)... ✓
Processing: French... ✓
Processing: German... ✓
Processing: Portuguese (Brazil)... ✓
Processing: Italian... ✓

[SUCCESS] Translation Complete!
[OUTPUT] 5 language versions created in to_qc/
[NEXT] Use CONFORM mode to check for English remnants

Core Features - v0.8a3-Enterprise

1. QC-A: Quality Check Analysis

Analyze subtitle files without modifications

CPL/CPS/Duration checks
Reading speed analysis
HTML/CSV reports
No file modifications

2. QC-FX: Quality Check & Fix

Analyze and automatically fix issues

All QC-A analysis
Automatic corrections
Frame grid alignment
Before/after reports

3. QC-DIFF: File Comparison

Compare original vs processed files

Visual diff highlighting
Timing analysis
Change tracking
Color-coded output

4. TRANS: Translation

Multi-language subtitle translation

Single to multiple languages
Language packages
Progress tracking
API integration

5. BT-QC: Back-Translation QC

Translation quality validation

Back-translation analysis
Similarity scoring
Quality assessment
Statistical reporting

6. CONFORM: Language Conforming

Fix mixed-language content

English remnant detection
Mixed script fixing
Sound effect translation
Consistency checking

7. SYNC: Transcript Sync

Match transcript to timing

Text-to-timing alignment
Fuzzy matching
Auto distribution
Confidence scoring

8. SRT-NAME: Language Naming

Detect and rename files

Auto language detection
Filename + content analysis
Batch renaming
108+ language support

9. BATCH-QC: Batch Processing

Process multiple files

Multi-file selection
Batch analysis/fix
Progress tracking
Summary reports

10. PIPELINE: Complete Workflow

Automated end-to-end

SDH to multi-language
Stage automation
Master reports
Production ready

11. ANALYSIS: Dashboard

Production analytics

File statistics
Quality scoring
Workflow insights
Comparative analysis

Installation & Setup

Quick Start

git clone https://github.com/growgoo/Babyl.git
cd Babyl
git checkout Babylphysh-08a3-Enterprise
pip install -r requirements.txt
python3 launch.py

API Configuration

Required: OpenAI API key for translation features

Edit data/api_config.csv:

provider,api_key,model
openai,sk-YOUR_API_KEY_HERE,gpt-3.5-turbo

Get your API key at: platform.openai.com/api-keys

Complete Version History

September 23, 2025

v0.8a3-Enterprise Current

Major Enhancements

Fixed all syntax errors and import dependencies
Enhanced SRT-NAME with advanced language detection
Improved workflow management and file selection
Professional package structure with proper initialization
Comprehensive error handling and logging
Production-ready deployment system

Critical Fixes

config.py syntax error (line 269) - RESOLVED
srt_name.py import issues - RESOLVED
__init__.py formatting errors - RESOLVED
workflow module dependencies - RESOLVED

New Features

Self-contained file selection in SRT-NAME
Filename + content language detection
Confidence scoring for detection accuracy
Batch language naming with selective processing
Professional rename preview and confirmation

September 2025

v0.8a2

Focus: Core Stability & Reporting

Enhanced HTML/CSV reporting system
Improved QC analysis algorithms
Frame rate detection capabilities
Basic batch processing implementation
Professional report templates

August 2025

v0.8a1

Focus: Foundation & Basic Functionality

Initial release of v0.8 series
Core QC functionality established
Basic translation support
SRT parsing and writing engines
Command-line interface framework

2024-2025

v0.7 Series

Focus: Prototype & Early Development

Proof of concept implementation
Basic mode structure design
Initial CLI interface
Early translation experiments
Core architecture planning

Forward Looking: v0.9 "Intelligence Enhanced"

Release Target: Q1 2026
Development Timeline: 8 weeks
Status: Planning Phase

Strategic Vision

Transform BabylPhysh from a fixed-API tool into a flexible AI-powered subtitle production platform where users select optimal AI models for different tasks. The flagship feature addresses critical ASR transcription errors through an innovative Hallucination Removal Engine.

Priority Features

CRITICAL: Hallucination Removal Engine

Problem: Whisper creates fictional dialogue during unclear audio, foreign speech, or background noise

Solution:

Manual marker detection [Hallucination begin/end]
User-defined replacement text
Batch correction across languages
Pattern analysis and detection
Timing preservation

Use Case: Documentary producer identifies 8 minutes of Tibetan speech that Whisper hallucinated as English dialogue. Marks sections, replaces with "[Tibetan speech]" across all 12 language versions in batch.

Multi-AI Model Selection

Choose Your Intelligence:

GPT-3.5 Turbo (fast, economical)
GPT-4 (high quality)
GPT-4 Turbo (balanced)
GPT-4o (latest model)
Real-time cost estimation
Quality vs cost optimization

Multi-Provider Support

Flexible API Integration:

OpenAI (current, enhanced)
Claude/Anthropic
Google Gemini
Azure OpenAI
Automatic failover
Cost comparison

Translation Memory

Consistency & Efficiency:

Remember previous translations
Terminology database
Context preservation
Auto-apply approved terms
Export/import memories

AI-Powered QC Enhancements

Intelligent Analysis:

Smart profile suggestions
Context-aware error detection
Cultural/linguistic checking
Hallucination pattern hints
Confidence scoring integration

Smart Batch Processing

Automated Optimization:

Automatic model selection
Load balancing across providers
Cost optimization strategies
Quality vs speed balancing
Batch hallucination correction

Development Timeline

Phase	Duration	Focus	Deliverables
Phase 1	Weeks 1-2	Foundation	Hallucination removal engine, Model selection framework, Enhanced configuration
Phase 2	Weeks 3-4	Provider Expansion	Claude/Gemini integration, Provider failover, Cost estimation engine
Phase 3	Weeks 5-6	Intelligence Features	Translation memory, AI-powered QC, Context-aware processing
Phase 4	Weeks 7-8	Advanced Features	Smart batch optimization, Enhanced analytics, Production reporting

Expected Benefits

Cost Optimization

30% cost reduction through smart model selection
Real-time cost estimation
Budget-aware processing

Quality Improvement

20% translation quality increase
95% hallucination removal accuracy
AI-powered error detection

Productivity Boost

40% workflow time reduction
Translation memory efficiency
Automated batch processing

Technical Specifications

System Requirements

Component	Minimum	Recommended
Python Version	3.8	3.10+
RAM	2GB	4GB+
Disk Space	500MB	1GB+
Internet	Required for API	Broadband

Supported File Formats

Input: SRT (SubRip Text) files
Output: SRT, HTML reports, CSV data
Encoding: UTF-8, Latin-1 (auto-detected)

API Integration

Provider	Status (v0.8a3)	Status (v0.9)
OpenAI	Active	Enhanced
Claude/Anthropic	—	Planned
Google Gemini	—	Planned
Azure OpenAI	—	Planned

Supported Languages

BabylPhysh supports 108+ languages via BCP47 language codes, including:

Essential Languages

English (US, UK)
Spanish (Latin America, Spain)
French
German
Portuguese (Brazil, Portugal)

Asian Languages

Japanese
Korean
Chinese (Simplified, Traditional)
Hindi
Thai, Vietnamese

European Languages

Italian, Dutch, Swedish
Polish, Czech, Hungarian
Norwegian, Danish, Finnish
Romanian, Bulgarian, Greek

Quick User Guide

Basic Workflow

Typical Documentary Production Pipeline:

Place English SDH file in masters/ folder
Run Mode 4 (TRANS) to generate multiple languages
Run Mode 6 (CONFORM) to fix partial translations
Run Mode 9 (BATCH-QC) for quality control
Use Mode 8 (SRT-NAME) to organize files
Generate final reports and deliver

Common Use Cases

1. Quick Quality Check

Launch: python3 launch.py
Select Mode 1 (QC-A)
Choose QC profile (FilmHub/Broadcast)
Select subtitle file
Review HTML report in output/reports/

2. Multi-Language Production

Launch: python3 launch.py
Select Mode 10 (PIPELINE)
Choose source SDH file
Select language package (Essential/Extended/Comprehensive)
Automatic translation + QC + reporting
Review master report for delivery status

3. Language Detection & Organization

Launch: python3 launch.py
Select Mode 8 (SRT-NAME)
Choose files to analyze (individual/range/all)
Review detected languages
Confirm batch rename
Files organized with language identifiers

Troubleshooting

Common Issues & Solutions:

Translation fails: Check API key in data/api_config.csv
Import errors: Ensure Python 3.8+ and dependencies installed
File not found: Verify file paths and folder structure
Encoding issues: BabylPhysh auto-detects UTF-8 and Latin-1

Contributing & Support

How to Contribute

Report bugs via GitHub Issues
Suggest features in Discussions
Submit pull requests with improvements
Help with documentation
Share your production workflows

Support Resources

Resource	Link
GitHub Repository	github.com/growgoo/Babyl
Issue Tracker	github.com/growgoo/Babyl/issues
Documentation	docs/ folder in repository
Current Branch	Babylphysh-08a3-Enterprise