TRAINING AND APPLYING PROSODY MODELS
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Abstract
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.
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Citations
34 Claims
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1-26. -26. (canceled)
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27. A computer-implementable method for synthesizing audible speech, with varying prosody, from textual content, the method comprising:
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maintaining an inventory of 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 different 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 the different segments of the text to produce prosody annotations for the text; considering annotations of the prosody annotations to reconcile conflicting prosody annotations due to multiple prosody models associated with a segment of the text; and synthesizing audible speech from the text and the reconciled prosody annotations. - View Dependent Claims (28, 29, 30, 31, 32, 33, 34)
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Specification