Glossary
Searchable terminology from accessibility, web standards, and related fields.
66 results found in machine learning.
- Automated speech scoring (Computer-aided speech assessment, Automatic speech evaluation)
- The use of computational techniques — including voice activity detection, phoneme recognition, prosody analysis, and speaker diarization — to automatically evaluate the accuracy and quality of speech …
- Automatic Sign Language Processing (ASLP, Sign Language Processing)
- An umbrella term encompassing three major areas of technology for sign language: automatic sign language generation (ASLG, creating sign language output from text or speech), automatic sign language r…
- Background Subtraction (Foreground-Background Separation, Background Modelling)
- Background subtraction is a computer vision technique used to identify moving objects (the foreground) in a video by comparing each frame against a model of the static background. Common approaches in…
- Bayesian Network (Bayes Network, Belief Network, Probabilistic Graphical Model)
- A statistical model that represents probabilistic relationships among variables using a directed graph structure. In accessibility and assistive technology applications, Bayesian networks are used for…
- Binary Classification (Two-Class Classification)
- A type of supervised machine learning task where the goal is to categorize items into one of exactly two classes. In accessibility research, binary classification has been applied to automatically det…
- Cascading classifier (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 whi…
- Continuous Sign Language Recognition (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 cli…
- Contrastive Decoding (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 co…
- Contrastive Learning (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)…
- Cross-Validation (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 a…
- Data Descriptor (Training Data Descriptor)
- An automated metric or feedback mechanism that characterizes the quality or properties of a dataset, particularly training images used in machine learning. In accessibility research, data descriptors …
- Data Representativeness (Dataset Representativeness, Demographic Representativeness)
- The degree to which a dataset reflects the diversity of the population it is intended to serve, particularly across demographic dimensions such as age, gender, race, ethnicity, disability, and socioec…
- Debiasing (Bias mitigation, Bias correction)
- Debiasing refers to techniques and processes applied to AI systems—particularly machine learning models and large language models—to detect, reduce, or eliminate unfair biases that cause the system to…
- Document Expansion (Query Prediction, Document Enrichment)
- An information retrieval technique that enhances a document by augmenting it with additional terms or predicted queries that users might use to search for that content. Methods like DocTTTTTQuery use …
- Dynamic Bayesian Network (DBN, Temporal Bayesian Network)
- A probabilistic graphical model that represents sequences of variables over time, extending standard Bayesian networks to handle temporal relationships. In accessibility and affective computing contex…
- Dynamic Programming (DP, DP Matching)
- A mathematical optimization technique used in pattern recognition that breaks complex problems into simpler overlapping subproblems. In accessibility technology, dynamic programming matching (DP match…
- Dynamic Time Warping (DTW)
- An algorithm for measuring similarity between two temporal sequences that may vary in speed or timing. Dynamic time warping aligns sequences by warping the time axis to find the optimal match, making …
- Feature Extraction (Feature Engineering, Representation Learning)
- Feature extraction is the process of identifying and isolating measurable properties or characteristics (features) from raw data such as images, audio, or text, for use in machine learning tasks. In i…
- Feature Hashing (Hashing Trick)
- A technique used in machine learning to convert text or categorical data into fixed-length numerical feature vectors by applying a hash function. Feature hashing is particularly useful for handling hi…
- Few-Shot Learning (N-Shot Learning, Low-Shot Learning)
- Few-shot learning is a machine learning approach that enables AI models to learn new concepts from only a small number of examples — typically 1 to 10 — rather than the hundreds or thousands tradition…