Glossary
Searchable terminology from accessibility, web standards, and related fields.
80 results found in Machine Learning.
- Large multimodal model (LMM, Multimodal AI, Vision-language model)
- An artificial intelligence model capable of processing and generating content across multiple modalities, such as text, images, and audio. Examples include GPT-4V and Gemini. In accessibility applicat…
- Layer-wise Relevance Propagation (LRP)
- Layer-wise Relevance Propagation (LRP) is an explainable AI technique that attributes a neural network's prediction back to its input features by propagating relevance scores layer by layer from the o…
- Learning Vector Quantization (LVQ)
- A supervised machine learning algorithm used for pattern classification, commonly applied in brain-computer interface systems to classify EEG signals. LVQ works by creating a set of reference vectors …
- Linear Discriminant Analysis (Fisher Discriminant Analysis, Fisherfaces)
- A statistical method used in pattern recognition and machine learning that finds a linear combination of features to best separate two or more classes of objects. In the context of face recognition, L…
- LoRA (Low-Rank Adaptation)
- A parameter-efficient fine-tuning technique, introduced by Hu et al. in 2022, in which a large pretrained neural network is specialised by training only a pair of small low-rank matrices that modify s…
- Mapping by Demonstration
- A personalisation technique for gestural and sensor-based interfaces in which the system learns the relationship between user input (movement, breath, gaze) and output (sound, visuals, commands) from …
- Meta-learning (Learning to Learn)
- A branch of machine learning where models are trained to learn new tasks from very few examples by leveraging knowledge gained from previous tasks. In accessibility applications, meta-learning enables…
- Mixture of Experts (MoE)
- Mixture of experts is a neural network architecture that routes each input through a small subset of specialist subnetworks ('experts') rather than activating the whole model. A gating network decides…
- Neural Radiance Field (NeRF)
- An implicit neural representation of a 3D scene, introduced by Mildenhall et al. in 2020, in which a small neural network is trained to map any 3D coordinate and viewing direction to a colour and dens…
- Neural Vocoder
- A deep-learning model that synthesises audio waveforms from intermediate acoustic representations such as mel-spectrograms or discrete speech units. Examples include HiFi-GAN, WaveNet, WaveGlow, and S…
- Object recognition (Object detection, Image classification)
- A computer vision task in which a system identifies and labels objects within images or video, often using deep learning models trained on large datasets. For blind and low-vision users, object recogn…
- On-device Recognition (On-Device Inference, Edge Recognition)
- Performing pattern recognition - such as sign language recognition, speech recognition, or computer vision - locally on the user's device rather than by sending input to a remote server. On-device rec…
- Open-Vocabulary Detection (Open-Vocabulary Object Detection, OVD)
- A class of computer vision object detection models that accept arbitrary text queries at inference time rather than being restricted to a fixed set of pre-trained classes. Instead of only recognizing,…
- OpenPose
- An open-source computer vision library developed by Carnegie Mellon University that detects human body, hand, facial, and foot keypoints in real-time from images or video. OpenPose extracts 25 body ke…
- Parameter-Efficient Fine-Tuning (PEFT, Lightweight Fine-Tuning)
- Parameter-efficient fine-tuning is a family of techniques (LoRA, adapters, prefix tuning, prompt tuning) that adapt a large pretrained model to a new task or domain by updating only a small fraction o…
- Part-of-Speech Tagging (POS Tagging, Grammatical Tagging)
- Part-of-speech tagging is the natural-language-processing task of labelling each word in a text with its grammatical category — noun, verb, adjective, and so on — using context from surrounding words.…
- Perceptual Linear Prediction (PLP, PLP Coefficients)
- Perceptual Linear Prediction (PLP) is an acoustic feature extraction technique used in speech processing that models human auditory perception. PLP analysis applies psychoacoustic principles including…
- Perplexity (Language Model Perplexity)
- A standard metric for evaluating language models that measures how well the model predicts a sample of text. Mathematically, perplexity is the inverse probability of the test set, normalised by the nu…
- Pointwise Mutual Information (PMI)
- A statistical measure used in natural language processing to quantify the strength of association between two words based on how much more frequently they co-occur in a corpus than would be expected b…
- Pose estimation (Body pose estimation, Human pose estimation)
- The computational process of determining the position and orientation of a person's body joints and limbs from sensor data such as cameras, depth sensors, or inertial measurement units. In accessibili…