Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: All-neural online source separation, counting, and diarization for
  meeting analysis   Automatic meeting analysis comprises the tasks of speaker counting, speaker
diarization, and the separation of overlapped speech, followed by automatic
speech recognition. This all has to be carried out on arbitrarily long sessions
and, ideally, in an online or block-online manner. While significant progress
has been made on individual tasks, this paper presents for the first time an
all-neural approach to simultaneous speaker counting, diarization and source
separation. The NN-based estimator operates in a block-online fashion and
tracks speakers even if they remain silent for a number of time blocks, thus
learning a stable output order for the separated sources. The neural network is
recurrent over time as well as over the number of sources. The simulation
experiments show that state of the art separation performance is achieved,
while at the same time delivering good diarization and source counting results.
It even generalizes well to an unseen large number of blocks.

25
The categories of this paper are: patt-sol
21
The categories of this paper are: adap-org
33
The categories of this paper are: plasm-ph
3
The categories of this paper are: physics
22
The categories of this paper are: chao-dyn
12
The categories of this paper are: nucl-th
8
The categories of this paper are: hep-ex
34
The categories of this paper are: chem-ph
0
The categories of this paper are: hep-ph
36
The categories of this paper are: cmp-lg
23
The categories of this paper are: solv-int
16
The categories of this paper are: stat
14
The categories of this paper are: math-ph
11
The categories of this paper are: hep-lat
30
The categories of this paper are: q-alg
13
The categories of this paper are: quant-ph