Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Towards Learning Fine-Grained Disentangled Representations from Speech   Learning disentangled representations of high-dimensional data is currently
an active research area. However, compared to the field of computer vision,
less work has been done for speech processing. In this paper, we provide a
review of two representative efforts on this topic and propose the novel
concept of fine-grained disentangled speech representation learning.

17
The categories of this paper are: q-fin
12
The categories of this paper are: nucl-th
10
The categories of this paper are: q-bio
37
The categories of this paper are: supr-con
22
The categories of this paper are: chao-dyn
3
The categories of this paper are: physics
24
The categories of this paper are: dg-ga
6
The categories of this paper are: astro-ph
9
The categories of this paper are: nlin
21
The categories of this paper are: adap-org
34
The categories of this paper are: chem-ph
30
The categories of this paper are: q-alg
31
The categories of this paper are: ao-sci
35
The categories of this paper are: mtrl-th
13
The categories of this paper are: quant-ph
18
The categories of this paper are: econ