1. A text-to-speech learning system, the system comprising: at least one processor; and at least one storage device, operatively connected to the at least one processor and storing: at least one training corpus comprising a plurality of training pairs that represent a varied vocabulary from one or more speakers, each training pair comprising a speech input and a text input corresponding to the speech input; and instructions that, when executed by the at least processor, cause the at least one processor to perform a method for generating a pronunciation sequence conversion model, the method comprising: for each training pair: selecting a training pair from the at least one training corpus; generating a first pronunciation sequence from the speech input of the training pair; and generating a second pronunciation sequence from the text input of the training pair; determining a pronunciation sequence difference between the first pronunciation sequence and the second pronunciation sequence; and generating a pronunciation sequence conversion model based on a plurality of pronunciation sequence differences, wherein the pronunciation sequence conversion model is configured to synthesize speech by converting a pronunciation sequence generated in response to a received speech input to a target pronunciation sequence that more closely matches a pronunciation sequence extracted from the received speech input.