Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: VisemeNet: Audio-Driven Animator-Centric Speech Animation   We present a novel deep-learning based approach to producing animator-centric
speech motion curves that drive a JALI or standard FACS-based production
face-rig, directly from input audio. Our three-stage Long Short-Term Memory
(LSTM) network architecture is motivated by psycho-linguistic insights:
segmenting speech audio into a stream of phonetic-groups is sufficient for
viseme construction; speech styles like mumbling or shouting are strongly
co-related to the motion of facial landmarks; and animator style is encoded in
viseme motion curve profiles. Our contribution is an automatic real-time
lip-synchronization from audio solution that integrates seamlessly into
existing animation pipelines. We evaluate our results by: cross-validation to
ground-truth data; animator critique and edits; visual comparison to recent
deep-learning lip-synchronization solutions; and showing our approach to be
resilient to diversity in speaker and language.

18
The categories of this paper are: econ
5
The categories of this paper are: gr-qc
8
The categories of this paper are: hep-ex
9
The categories of this paper are: nlin
12
The categories of this paper are: nucl-th
16
The categories of this paper are: stat
20
The categories of this paper are: acc-phys
30
The categories of this paper are: q-alg
32
The categories of this paper are: atom-ph
24
The categories of this paper are: dg-ga
11
The categories of this paper are: hep-lat
7
The categories of this paper are: hep-th
28
The categories of this paper are: alg-geom
37
The categories of this paper are: supr-con
15
The categories of this paper are: nucl-ex
4
The categories of this paper are: cond-mat