Release and Version History¶

x.y.z (Backlog)¶

Features and Improvements

Minor Improvements

Bugfixes

Miscellaneous

Features and Improvements

Core Transcription Engine: Built on faster-whisper for high-accuracy audio-to-text conversion
Parallel Processing: Automatic audio segmentation with multi-CPU core processing for exceptional speed
Smart Audio Segmentation: Intelligent chunking of large audio files by duration or segment count
Multi-Format Support: Handles popular audio formats including MP3, MP4, WAV, M4A, FLAC, OGG
Automatic Language Detection: AI-powered language detection without manual specification
Command Line Interface: Simple CLI with audinota transcribe –input=”file.mp3” syntax
Flexible Output Management: Support for directory output, custom file naming, and automatic conflict resolution
Cost-Effective Solution: 120x cheaper than AWS Transcribe when deployed on cloud infrastructure

CLI Features

Smart Output Resolution: Automatic .txt file creation next to input files when no output specified
Directory Output Support: Batch processing with organized output to specified directories
File Conflict Handling: Automatic numbering for directory outputs, overwrite protection for file outputs
Real-time Progress Feedback: Emoji-enhanced status updates during transcription process
Multiple Input Format Detection: Seamless handling of various audio/video formats

Python API

Simple Integration: Clean API with transcribe_audio_in_parallel() function
Audio Utility Functions: Duration calculation, segmentation by count/duration
Streaming Support: BytesIO input support for in-memory audio processing
Performance Optimization: Built-in parallel processing for large audio files

Documentation and Usability

Comprehensive README: Detailed usage examples, CLI documentation, and cost comparison
Real-world Examples: Practical use cases for researchers, content creators, and data analysts
Performance Benchmarking: Speed and cost comparisons with commercial transcription services