Training and applying prosody models

摘要

Techniques for training and applying prosody models for speech synthesis are provided. A speech recognition engine processes audible speech to produce text annotated with prosody information. A prosody model is trained with this annotated text. After initial training, the model is applied during speech synthesis to generate speech with non-standard prosody from input text. Multiple prosody models can be used to represent different prosody styles.

主权项

1. A computer-implementable method for synthesizing audible speech, with varying prosody, from textual content, the method comprising:
generating texts annotated with prosody information generated from audio using a speech recognition engine that performs the annotation during its operation; training prosody models with lexicons based on first segments of the texts with the prosody information; maintaining an inventory of the prosody models with lexicons, selecting a subset of multiple prosody models from the inventory of prosody models; associating prosody models in the subset of multiple prosody models with second segments of a text based on phrases in the text statistically associated with the lexicons of the prosody models; applying the associated prosody models to one of the second segments of the text to produce prosody annotations for the text; updating the associated prosody models' lexicons based on the phrases in the second segments of text; analyzing annotations of the prosody annotations to reconcile conflicting prosody annotations previously produced by multiple prosody models associated with the second segments of text; and synthesizing audible speech from the second segments of text and the reconciled prosody annotations.