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. 2. The method of claim 1 , wherein each given colloquial-speaker vector of each respective set of colloquial-speaker vectors has an associated enriched transcription derived from a respective text string associated with a particular recorded colloquial speech utterance from which the given colloquial-speaker vector was extracted, and wherein replacing each colloquial-speaker vector of the respective set of colloquial-speaker vectors with the respective, optimally-matched reference-speaker vector comprises: for each given colloquial-speaker vector of the respective set of colloquial-speaker vectors that is replaced, retaining its associated enriched transcription.