3.2. Preprocessing

We use linear spectrograms which can be obtained from
raw waveforms through the Short-time Fourier transform
(STFT), as input of the posterior encoder. The FFT size,
window size and hop size of the transform are set to 1024,
1024 and 256, respectively. We use 80 bands mel-scale
spectrograms for reconstruction loss, which is obtained by
applying a mel-ﬁlterbank to linear spectrograms.
We use International Phonetic Alphabet (IPA) sequences as
input to the prior encoder. We convert text sequences to IPA
phoneme sequences using open-source software (Bernard,
2021), and the converted sequences are interspersed with a
blank token following the implementation of Glow-TTS.

3.3. Training
ConditionalVariationalAutoencoderwithAdversarialLearningfor End-to-EndText-to-Speech