Abstract:
A method for synthesizing speech from text includes receiving one or more waveforms characteristic of a voice of a person selected by a user, generating a personalized voice font based on the one or more waveforms, and delivering the personalized voice font to the user's computer, whereby speech can be synthesized from text, the speech being in the voice of the selected person, the speech being synthesized using the personalized voice font. A system includes a text-to-speech (TTS) application operable to generate a voice font based on speech waveforms transmitted from a client computer remotely accessing the TTS application.
Abstract:
A method and apparatus are provided for refining segmental boundaries in speech waveforms. Contextual acoustic feature similarities are used as a basis for clustering adjacent phoneme speech units, where each adjacent pair phoneme speech units include a segmental boundary. A refining model is trained for each cluster and used to refine boundaries of contextual phoneme speech units forming the clusters.
Abstract:
A method is provided for optimizing an objective measure used to estimate mean opinion score or naturalness of synthesized speech from a speech synthesizer. The method includes using an objective measure that has components derived directly from textual information used to form synthesized utterances. The objective measure has a high correlation with mean opinion score such that a relationship can be formed between the objective measure and corresponding mean opinion score. The objective measure is altered to provide a different function of textual information derived from the utterances so as to improve the relationship between the scores of the objective measure and subjective ratings of the synthesized utterances.
Abstract:
A concatenating speech synthesizer concatenates selected speech units to obtain the desired synthesized speech. When desired speech units of phonetic and/or prosodic context are not available, the synthesizer selects replacement speech units based on measures representative of the difference between the HMM acoustic models of the desired speech unit and available speech units.
Abstract:
A method for identifying common multiphone units to add to a unit inventory for a text-to-speech generator is disclosed. The common multiphone units are units that are larger than a phone, but smaller than a syllable. The method slices each syllable into a plurality of slices. These slices are then sorted and the frequency of each slice is determined. Those slices whose frequencies exceed a threshold are added to the unit inventory. The remaining slices are decomposed according to a predetermined set of rules to determine if they contain slices that should be added to the unit inventory.
Abstract:
Described is a technology by which synthesized speech generated from text is evaluated against a prosody model (trained offline) to determine whether the speech will sound unnatural. If so, the speech is regenerated with modified data. The evaluation and regeneration may be iterative until deemed natural sounding. For example, text is built into a lattice that is then (e.g., Viterbi) searched to find a best path. The sections (e.g., units) of data on the path are evaluated via a prosody model. If the evaluation deems a section to correspond to unnatural prosody, that section is replaced, e.g., by modifying/pruning the lattice and re-performing the search. Replacement may be iterative until all sections pass the evaluation. Unnatural prosody detection may be biased such that during evaluation, unnatural prosody is falsely detected at a higher rate relative to a rate at which unnatural prosody is missed.
Abstract:
A method and apparatus are provided for refining segmental boundaries in speech waveforms. Contextual acoustic feature similarities are used as a basis for clustering adjacent phoneme speech units, where each adjacent pair phoneme speech units include a segmental boundary. A refining model is trained for each cluster and used to refine boundaries of contextual phoneme speech units forming the clusters.
Abstract:
A method is provided for optimizing an objective measure used to estimate mean opinion score or naturalness of synthesized speech from a speech synthesizer. The method includes using an objective measure that has components derived directly from textual information used to form synthesized utterances. The objective measure has a high correlation with mean opinion score such that a relationship can be formed between the objective measure and corresponding mean opinion score. The objective measure is altered to provide a different function of textual information derived from the utterances so as to improve the relationship between the scores of the objective measure and subjective ratings of the synthesized utterances.
Abstract:
A text processing system for processing multi-lingual text for a speech synthesizer includes a first language dependent module for performing at least one of text and prosody analysis on a portion of input text comprising a first language. A second language dependent module performs at least one of text and prosody analysis on a second portion of input text comprising a second language. A third module is adapted to receive outputs from the first and second dependent module and performs prosodic and phonetic context abstraction over the outputs based on multi-lingual text.
Abstract:
A method for identifying common multiphone units to add to a unit inventory for a text-to-speech generator is disclosed. The common multiphone units are units that are larger than a phone, but smaller than a syllable. The method slices each syllable into a plurality of slices. These slices are then sorted and the frequency of each slice is determined. Those slices whose frequencies exceed a threshold are added to the unit inventory. The remaining slices are decomposed according to a predetermined set of rules to determine if they contain slices that should be added to the unit inventory.