Abstract: A system and method of converting source speech to target speech using intermediate speech data is disclosed. The method comprises identifying intermediate speech data that match target voice training data based on acoustic features; performing dynamic time warping to match the second set of acoustic features of intermediate speech data and the first set of acoustic features of target voice training data; training a neural network to convert the intermediate speech data to target voice training data; receiving source speech data; converting the source speech data to an intermediate speech; converting the intermediate speech to a target speech sequence using the neural network; and converting the target speech sequence to target speech using the pitch from the target voice training data.

Abstract: A system and method for converting text to speech is disclosed. The text is decomposed into a sequence of phonemes and a text feature matrix constructed to define the manner in which the phonemes are pronounced and accented. A spectrum generator then queries a neural network to produce normalized spectrograms based on the input of the sequence of phonemes and features. Normalized spectrograms are fixed-length spectrograms with uniform temporal length (i.e., data size), which enables them to be effectively encoded into a neural network representation. A duration generator output a plurality of durations that are associated with phonemes. A speech synthesizer modifies the temporal length (i.e., de-normalizes) of each normalized spectrogram based on the associated duration, and then combines the plurality of modified spectrograms into speech.

Abstract: A system and method of converting source speech to target speech using intermediate speech data is disclosed. The method comprises identifying intermediate speech data that match target voice training data based on acoustic features; performing dynamic time warping to match the second set of acoustic features of intermediate speech data and the first set of acoustic features of target voice training data; training a neural network to convert the intermediate speech data to target voice training data; receiving source speech data; converting the source speech data to an intermediate speech; converting the intermediate speech to a target speech sequence using the neural network; and converting the target speech sequence to target speech using the pitch from the target voice training data.