Tacotron 2

2000년 도입 · 논문 23편에서 사용

Tacotron 2 is a neural network architecture for speech synthesis directly from text. It consists of two components: - a recurrent sequence-to-sequence feature prediction network with attention which predicts a sequence of mel spectrogram frames from an input character sequence - a modified version of WaveNet which generates time-domain waveform samples conditioned on the predicted mel spectrogram frames In contrast to the original Tacotron, Tacotron 2 uses simpler building blocks, using vanilla LSTM and convolutional layers in the encoder and decoder instead of CBHG stacks and GRU recurrent layers. Tacotron 2 does not use a “reduction factor”, i.e., each decoder step corresponds to a single spectrogram frame. Location-sensitive attention is used instead of additive attention.

출처: Natural TTS Synthesis by Conditioning WaveNet on Mel Spectrogram Predictions

소개 논문: Natural TTS Synthesis by Conditioning WaveNet on Mel Spectrogram Predictions