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Lecture 17 - Speaker verification

This is the first of two lectures on speaker recognition. Speaker recognition includes a number of different tasks: speaker verification (determine if test speaker matches a specific target speaker), speaker identification (determine which of a set of enrolled speakers a test speaker matches), and speaker diarization (determine "who spoke when" in a recording). This lecture concerns speaker verification, the next lecture concerns speaker diarization.

Hansen and Hasan (2015) provide a tutorial overview on Speaker Recognition by Machines and Humans; for i-vectors, Dehak et al (2011) is probably still the best reference (Front-End Factor Analysis for Speaker Verification); for neural network x-vector approaches see Snyder et al (2018), X-Vectors: Robust DNN Embeddings for Speaker Recognition.

Speaker verfication

GMM-based speaker verification

i-Vectors

Neural network approcahes


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