Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Learning Joint Articulatory-Acoustic Representations with Normalizing
  Flows   The articulatory geometric configurations of the vocal tract and the acoustic
properties of the resultant speech sound are considered to have a strong causal
relationship. This paper aims at finding a joint latent representation between
the articulatory and acoustic domain for vowel sounds via invertible neural
network models, while simultaneously preserving the respective domain-specific
features. Our model utilizes a convolutional autoencoder architecture and
normalizing flow-based models to allow both forward and inverse mappings in a
semi-supervised manner, between the mid-sagittal vocal tract geometry of a two
degrees-of-freedom articulatory synthesizer with 1D acoustic wave model and the
Mel-spectrogram representation of the synthesized speech sounds. Our approach
achieves satisfactory performance in achieving both articulatory-to-acoustic as
well as acoustic-to-articulatory mapping, thereby demonstrating our success in
achieving a joint encoding of both the domains.

20
The categories of this paper are: acc-phys
32
The categories of this paper are: atom-ph
35
The categories of this paper are: mtrl-th
7
The categories of this paper are: hep-th
2
The categories of this paper are: math
28
The categories of this paper are: alg-geom
0
The categories of this paper are: hep-ph
33
The categories of this paper are: plasm-ph
21
The categories of this paper are: adap-org
18
The categories of this paper are: econ
10
The categories of this paper are: q-bio
6
The categories of this paper are: astro-ph
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The categories of this paper are: math-ph
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The categories of this paper are: chao-dyn
3
The categories of this paper are: physics
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The categories of this paper are: patt-sol