Automatic Prosody Annotation with Pre-Trained Text-Speech Model. (arXiv:2206.07956v1 [cs.SD])

Web: http://arxiv.org/abs/2206.07956

Prosodic boundary plays an important role in text-to-speech synthesis (TTS)
in terms of naturalness and readability. However, the acquisition of prosodic
boundary labels relies on manual annotation, which is costly and
time-consuming. In this paper, we propose to automatically extract prosodic
boundary labels from text-audio data via a neural text-speech model with
pre-trained audio encoders. This model is pre-trained on text and speech data
separately and jointly fine-tuned on TTS data in a triplet format: {speech,
text, prosody}. The experimental …

annotation arxiv model speech text