Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Adaptive blind audio source extraction supervised by dominant speaker
  identification using x-vectors   We propose a novel algorithm for adaptive blind audio source extraction. The
proposed method is based on independent vector analysis and utilizes the
auxiliary function optimization to achieve high convergence speed. The
algorithm is partially supervised by a pilot signal related to the source of
interest (SOI), which ensures that the method correctly extracts the utterance
of the desired speaker. The pilot is based on the identification of a dominant
speaker in the mixture using x-vectors. The properties of the x-vectors
computed in the presence of cross-talk are experimentally analyzed. The
proposed approach is verified in a scenario with a moving SOI, static
interfering speaker, and environmental noise.

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The categories of this paper are: nlin
36
The categories of this paper are: cmp-lg
33
The categories of this paper are: plasm-ph
32
The categories of this paper are: atom-ph
37
The categories of this paper are: supr-con
3
The categories of this paper are: physics
35
The categories of this paper are: mtrl-th
20
The categories of this paper are: acc-phys
29
The categories of this paper are: funct-an
30
The categories of this paper are: q-alg
25
The categories of this paper are: patt-sol
2
The categories of this paper are: math
23
The categories of this paper are: solv-int
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The categories of this paper are: astro-ph
0
The categories of this paper are: hep-ph
10
The categories of this paper are: q-bio