Building and Freezing an AI Humanization Pipeline
The author created a post-processing pipeline to add human-like elements to AI-generated text, but ultimately decided to freeze the code due to issues with register and Japanese honorifics.
Why it matters
Properly handling language nuances and register is critical for developing human-like AI communication systems.
Key Points
- 1The pipeline included filler injection, typo injection, and rhythm variation to make text more human-like
- 2The pipeline treated all text the same way, regardless of register (formal/business/casual/friendly)
- 3The pipeline did not properly handle Japanese honorifics (respectful, humble, and polite language)
Details
The author developed a pipeline called 'humanize/pipeline.py' that consisted of three stages: filler injection, typo injection, and rhythm variation. The goal was to integrate this pipeline into a production environment for human-like AI communication. However, the author soon realized that the pipeline was fundamentally flawed. It processed all text the same way, without any distinction for register or formality level. This was particularly problematic for Japanese, where the honorific system (respectful, humble, and polite language) is crucial for appropriate communication. The author concluded that the pipeline was not ready for real-world use and decided to freeze the code.
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