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Probing the phonetic and phonological knowledge of tones in Mandarin TTS models

2019-12-23 · Jian Zhu

This study probes the phonetic and phonological knowledge of lexical tones in TTS models through two experiments. Controlled stimuli for testing tonal coarticulation and tone sandhi in Mandarin were fed into Tacotron 2 and WaveGlow to generate speech samples, which were subject to acoustic analysis and human evaluation. Results show that both baseline Tacotron 2 and Tacotron 2 with BERT embeddings capture the surface tonal coarticulation patterns well but fail to consistently apply the Tone-3 sandhi rule to novel sentences. Incorporating pre-trained BERT embeddings into Tacotron 2 improves the naturalness and prosody performance, and yields better generalization of Tone-3 sandhi rules to novel complex sentences, although the overall accuracy for Tone-3 sandhi was still low. Given that TTS models do capture some linguistic phenomena, it is argued that they can be used to generate and validate certain linguistic hypotheses. On the other hand, it is also suggested that linguistically informed stimuli should be included in the training and the evaluation of TTS models.

📄 PDF Abstract BibTeX arXiv:1912.10915

Code (1)

lingjzhu/probing-TTS-models 공식 구현 pytorch

Methods 이 논문이 사용한 방법론

Dilated Causal Convolution A Dilated Causal Convolution is a causal convolution where the filter is applied over an area larger than its length by…
Zoneout Zoneout is a method for regularizing RNNs. At each timestep, zoneout stochastically forces some…
LSTM An LSTM is a type of recurrent neural network that addresses the vanishing gradient problem in vanilla…
WaveNet WaveNet is an audio generative model based on the PixelCNN architecture. In order to deal with long-range temporal dependencies…
Mixture of Logistic Distributions 설명 없음
Location Sensitive Attention Location Sensitive Attention is an attention mechanism that extends the additive attention mechanism to use cumulative…
BiLSTM A Bidirectional LSTM, or biLSTM, is a sequence processing model that consists of two LSTMs: one taking the input in a forward direction, and the other in a backwards…
Linear Layer A Linear Layer is a projection $\mathbf{XW + b}$.

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