#contextual biasing
4 related articles
·3 min
Technical Terms Getting Transliterated in Multilingual Speech Recognition? Four Solutions Explained
When Korean/Japanese ASR transliterates GitHub as 기터부 or ギットハブ, what can developers do? This article analyzes four solutions: correction dictionaries, hotword biasing, model fine-tuning, and more.
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·3 min
Bias and Double Standards in AI Content Moderation: Technical Roots and Solutions
An in-depth analysis of bias and double standards in AI content moderation systems, exploring technical roots including training data flaws, annotation subjectivity, and rule design issues, with solutions for building fairer systems.
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·5 min
In-Depth Analysis of the GPT-5.6 EQ Test: Progress and Limitations in Emotional Intelligence
A Reddit user ran EQ tests on ChatGPT 5.5 and 5.6, covering meeting emotion ranking, chess-behavior judgment, and facial attractiveness. Version 5.6 shows clear gains in multimodal emotional understanding, but social common sense remains a core weakness.
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·6 min
AI Superforecasters: Can Machines Surpass Human Experts at Prediction?
Have AI superforecasters truly arrived? A deep dive into how LLMs challenge human superforecasters in probability calibration, information integration, and scalable forecasting, plus core debates on data leakage, interpretability, and real-world applications.
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