Glossary

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Calibration-Free Interface(also: Zero-Shot Interface, Plug-and-Play Interface, Cross-User Model)

An input system that works for a new user without any per-user training or calibration data, typically by relying on models trained on large multi-user datasets that capture enough physiological and behavioural variation to generalise. Voice assistants and mixed-reality hand…

Camera-based assistive technology(also: Camera-based AT, Vision-based AT, VBAT)

Assistive technologies that use cameras (typically smartphone cameras or smart glasses) combined with computer vision and AI to provide visual information to blind and low-vision users. Applications include object recognition, text reading (OCR), scene description, face…

Cascading classifier(also: Cascaded detection, Multi-stage classifier)

A machine learning architecture that chains multiple detection stages in sequence, where each stage filters candidates before passing them to the next, progressively increasing detection precision while maintaining recall. In accessibility applications, cascading classifiers are…

Chain-of-Thought(also: CoT, Chain of Thought Reasoning, Step-by-Step Reasoning)

Chain-of-thought is a prompting and model-design technique in which a large language model produces its intermediate reasoning steps before giving a final answer. Modern reasoning models (e.g., OpenAI o-series, Claude thinking modes) expose chain-of-thought as visible internal…

Clustering Algorithm(also: Cluster Analysis, Unsupervised Clustering, K-means)

A clustering algorithm is an unsupervised machine-learning technique that groups similar data points together based on a distance or similarity measure, without needing pre-labelled training data. Common algorithms include K-means, PAM (Partitioning Around Medoids), CLARA…

Confidence score(also: Certainty score, Prediction confidence)

A numerical value (typically 0-100% or 0-1) indicating how certain an AI system is about its prediction or classification. In accessibility contexts, communicating confidence scores to users — particularly blind users who cannot visually verify AI output — helps them calibrate…

Constitutional AI(also: CAI)

A training method introduced by Anthropic in 2022 in which a large language model is aligned to a written set of principles (a 'constitution') through self-critique and reinforcement learning from AI feedback, rather than relying exclusively on human preference labels. The model…

Continual Learning(also: Continuous Learning, Lifelong Learning, Never-ending Learning)

A machine learning paradigm in which models learn incrementally from new data over time while retaining previously acquired knowledge, rather than being trained once on a fixed dataset. Continual learning is relevant to accessibility because it enables AI-powered accessibility…

Continuous Sign Language Recognition(also: CSLR)

A computer vision task that involves recognizing sign language from continuous, naturally produced signing — as opposed to isolated sign recognition, which identifies individual signs in segmented clips. Continuous sign language recognition deals with the complexities of natural…

Contrastive Decoding(also: Visual Contrastive Decoding, VCD)

Contrastive decoding is a technique for reducing hallucinations in large language model and multimodal AI outputs by comparing token probability distributions across different input conditions. The core principle is that tokens genuinely grounded in the input content will change…

Contrastive Learning(also: Contrastive Self-Supervised Learning)

Contrastive learning is a machine learning technique that trains models to produce vector embeddings by maximising similarity between representations of the same or augmented instance (positive pairs) while minimising similarity between representations of different instances…

Convolutional Neural Network(also: CNN, ConvNet)

A class of deep neural network that uses convolutional filters to automatically extract spatial features from data, originally designed for image processing but now widely applied to sensor data, audio, and video analysis. CNNs identify patterns like edges, textures, and shapes…

Counterfactual Explanation(also: Counterfactual XAI)

An explanation technique that communicates what minimal change to the input would have produced a different output from an AI model, for example 'if the applicant's income had been $5,000 higher, the loan would have been approved'. Counterfactual explanations are legally…

Cross-Validation(also: K-Fold Cross-Validation, Stratified Cross-Validation)

A statistical method for evaluating machine learning models by splitting data into multiple subsets (folds), training the model on some folds and testing on the remaining ones, then rotating through all combinations. Stratified cross-validation ensures each fold maintains the…

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