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RSS Curriculum Vitae TR

Embedding

Turkish equivalent: Gömme vektörüDomain: Machine Learning

A learned dense vector representation in which geometric proximity is intended to preserve task-relevant similarity or structure.

Representation Space

An embedding maps an object such as text, an image, audio or an identity sample into a fixed-dimensional vector. The useful meaning comes from the training objective and data, not from the vector coordinates individually.

Similarity can then be computed with cosine, dot product or another metric appropriate to the model.

Operational Boundary

Embedding distance is model- and domain-dependent. A universal similarity threshold should not be assumed across model versions or data sources.

Large embedding collections are often indexed with approximate-nearest-neighbor structures such as HNSW.

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Related concepts

Machine Learning

Related technical publications

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Speaker Recognition and Diarization

Speaker verification and identification, text-dependent and text-independent recognition, GMM-UBM, i-vectors, speaker embeddings, threshold calibration, and diarization.

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