Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: DRSpeech: Degradation-Robust Text-to-Speech Synthesis with Frame-Level
  and Utterance-Level Acoustic Representation Learning   Most text-to-speech (TTS) methods use high-quality speech corpora recorded in
a well-designed environment, incurring a high cost for data collection. To
solve this problem, existing noise-robust TTS methods are intended to use noisy
speech corpora as training data. However, they only address either
time-invariant or time-variant noises. We propose a degradation-robust TTS
method, which can be trained on speech corpora that contain both additive
noises and environmental distortions. It jointly represents the time-variant
additive noises with a frame-level encoder and the time-invariant environmental
distortions with an utterance-level encoder. We also propose a regularization
method to attain clean environmental embedding that is disentangled from the
utterance-dependent information such as linguistic contents and speaker
characteristics. Evaluation results show that our method achieved significantly
higher-quality synthetic speech than previous methods in the condition
including both additive noise and reverberation.

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The categories of this paper are: math
5
The categories of this paper are: gr-qc
17
The categories of this paper are: q-fin
35
The categories of this paper are: mtrl-th
0
The categories of this paper are: hep-ph
13
The categories of this paper are: quant-ph
32
The categories of this paper are: atom-ph
24
The categories of this paper are: dg-ga
9
The categories of this paper are: nlin
36
The categories of this paper are: cmp-lg
34
The categories of this paper are: chem-ph
7
The categories of this paper are: hep-th
29
The categories of this paper are: funct-an
12
The categories of this paper are: nucl-th
21
The categories of this paper are: adap-org
6
The categories of this paper are: astro-ph