Glossary Library

Technical GlossarySpeech, Voice and Audio AI

Speaker Embeddings

Dense vector representations that capture speaker identity in a discriminative form.

Speaker embeddings form the basis of modern speaker recognition systems. The goal is to place samples from the same person close together and samples from different people far apart in vector space. This supports verification, clustering, and diarization workflows alike. It is one of the key representations that makes voice biometrics scalable and flexible.

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Representation Learning

An approach in which informative, discriminative, and task-relevant internal representations are learned automatically from raw data.

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Non-negative Matrix Factorization

A dimensionality reduction technique that produces part-based and interpretable representations in non-negative data.

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Autoencoder-Based Dimensionality Reduction

An approach that learns lower-dimensional representations of data through neural-network-based compression.