Training and applying prosody models
AssigneeMorphism LLC
InventorJames H. Stephens, Jr.
Life of this patent
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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.
Claims13
A computer-implementable method for synthesizing audible speech, with varying prosody, from textual content, the method comprising:
- building an inventory of prosody models with designated characteristics;
- selecting a target prosody model for training based on input parameters and first keywords related to a first text segment of a first text with prosody annotations;
- training the target prosody models based on the prosody annotations of the first text segment;
- maintaining associations between the first keywords, the designated characteristics, and the input characteristics;
- selecting multiple prosody models for application for a second text segment of a second text based on second keywords related to the second text and the associations;
- applying the multiple application prosody models to the second text segment;
- reconciling conflicts from the application of the multiple application prosody models to generate reconciled prosody information;
- and
- generating audible speech for the second text segment based on the reconciled prosody information using a text-to-speech synthesis engine.
A system for synthesizing audible speech, with varying prosody, from textual content, the system comprising:
- a non-transitory memory for storing instructions;
- instructions stored on the non-transitory memory, the instructions executable on a processor to:
- build an inventory of prosody models with designated characteristics;
- select a target prosody model for training based on input parameters and first keywords related to a first text segment of a first text with prosody annotations;
- train the target prosody models based on the prosody annotations of the first text segment;
- use associations between the first keywords, the designated characteristics, and the input characteristics;
- select multiple prosody models for application for a second text segment of a second text based on second keywords related to the second text segment and the associations;
- apply the multiple application prosody models to the second text;
- reconcile conflicts from the application of the multiple application prosody models to generate reconciled prosody information and a speech synthesis engine that generates audible speech for the second text segment based on the reconciled prosody information using a text-to-speech synthesis engine.
Dependencies are inferred from the claim text.