1. A method comprising: extracting speech features from a plurality of recorded reference speech utterances of a reference speaker to generate a reference set of reference-speaker vectors; for each respective plurality of recorded colloquial speech utterances of a respective colloquial speaker of multiple colloquial speakers, extracting speech features from the recorded colloquial speech utterances of the respective colloquial speaker to generate a respective set of colloquial-speaker vectors; for each respective set of colloquial-speaker vectors, replacing each colloquial-speaker vector of the respective set of colloquial-speaker vectors with a respective, optimally-matched reference-speaker vector from among the reference set of reference-speaker vectors, the respective, optimally-matched reference-speaker vector being identified by matching under a transform that compensates for differences in speech between the reference speaker and the respective colloquial speaker; aggregating the replaced colloquial-speaker vectors of all the respective sets of colloquial-speaker vectors into an aggregate set of conditioned speaker vectors; providing the aggregate set of conditioned speaker vectors to a text-to-speech (TTS) system implemented on one or more computing devices; and training the TTS system using the provided aggregate set of conditioned speaker vectors.
1. A method comprising: extracting speech features from a plurality of recorded reference speech utterances of a reference speaker to generate a reference set of reference-speaker vectors; for each respective plurality of recorded colloquial speech utterances of a respective colloquial speaker of multiple colloquial speakers, extracting speech features from the recorded colloquial speech utterances of the respective colloquial speaker to generate a respective set of colloquial-speaker vectors; for each respective set of colloquial-speaker vectors, replacing each colloquial-speaker vector of the respective set of colloquial-speaker vectors with a respective, optimally-matched reference-speaker vector from among the reference set of reference-speaker vectors, the respective, optimally-matched reference-speaker vector being identified by matching under a transform that compensates for differences in speech between the reference speaker and the respective colloquial speaker; aggregating the replaced colloquial-speaker vectors of all the respective sets of colloquial-speaker vectors into an aggregate set of conditioned speaker vectors; providing the aggregate set of conditioned speaker vectors to a text-to-speech (TTS) system implemented on one or more computing devices; and training the TTS system using the provided aggregate set of conditioned speaker vectors. 4. The method of claim 1 , wherein, for each respective set of colloquial-speaker vectors, replacing each colloquial-speaker vector of the respective set of colloquial-speaker vectors with the respective, optimally-matched reference-speaker vector from among the reference set of reference-speaker vectors comprises: individually matching all of the colloquial-speaker vectors of each respective set with their respective, optimally-matched reference-speaker vectors, one respective set at a time.