Abstract: A technique to enhance the quality of Text-to-Speech (TTS) based Singing Voice generation is disclosed. The present invention efficiently preserves the speaker identity and improves sound quality by incorporating speaker-independent natural singing information into TTS-based Speech-to-Singing (STS). The Template-based Text-to-Singing (TTTS) system merges qualities of a singing voice generated from a TTS system with qualities of a singing voice generated from an actual voice singing the song. The qualities are represented in terms of Mel-generalized cepstrum (MGC) coefficients. In particular, low-order MGC coefficients from the TTS-based singing voice with high-order MGC coefficients from the voice of an actual singer.

Abstract: A vehicle includes a vehicle subsystem, a user interface, and a controller. The user interface is configured to display a plurality of selectable vehicle models. The controller is programmed to, in response to a selection of a particular vehicle model, adjust a parameter of the subsystem to emulate a corresponding subsystem parameter of the particular vehicle model.

Abstract: A method and system for converting a source voice to a target voice is disclosed. The method comprises: recording source voice data and target voice data; extracting spectral envelope features from the source voice data and target voice data; time-aligning pairs of frames based on the extracted spectral envelope features; converting each pair of frames into a frequency domain; generating a plurality of frequency-warping factor candidates, wherein each of the plurality of frequency-warping factor candidates is associated with one of the pairs of frames; generating a single global frequency-warping factor based on the candidates; acquiring source speech; converting the source speech to target speech based on the global frequency-warping factor; generating a waveform comprising the target speech; and playing the waveform comprising the target speech to a user.

Abstract: A voice coder configured to resolve periodic and aperiodic components of spectra is disclosed. The method of voice coding includes parsing the speech signal into a plurality of speech frames; for each of the plurality of speech frames: (a) generating the spectra for the speech frame, (b) parsing the spectra of the speech frame into a plurality of sub-bands, (c) transforming each of the plurality of sub-bands into a time-domain envelope signal, and (d) generating a plurality of sub-band voicing factors, wherein each sub-band voicing factor indicates the harmonicity of one of the plurality of sub-bands, and each sub-band voicing factor is based on the periodicity of one of said time-domain envelope signals associated with one of the plurality of sub-bands.

Abstract: A vehicle includes a vehicle subsystem, a user interface, and a controller. The user interface is configured to display a plurality of selectable vehicle models. The controller is programmed to, in response to a selection of a particular vehicle model, adjust a parameter of the subsystem to emulate a corresponding subsystem parameter of the particular vehicle model.

Abstract: In voice processing, a first distribution generation unit approximates a distribution of feature information representative of voice of a first speaker per a unit interval thereof as a mixed probability distribution which is a mixture of a plurality of first probability distributions corresponding to a plurality of different phones. A second distribution generation unit also approximates a distribution of feature information representative of voice of a second speaker as a mixed probability distribution which is a mixture of a plurality of second probability distributions. A function generation unit generates, for each phone, a conversion function for converting the feature information of voice of the first speaker to that of the second speaker based on respective statistics of the first and second probability distributions that correspond to the phone.

Abstract: In a voice processing apparatus, a processor performs generating a converted feature by applying a source feature of source voice to a conversion function, generating an estimated feature based on a probability that the source feature belongs to each element distribution of a mixture distribution model that approximates distribution of features of voices having different characteristics, generating a first conversion filter based on a difference between a first spectrum corresponding to the converted feature and an estimated spectrum corresponding to the estimated feature, generating a second spectrum by applying the first conversion filter to a source spectrum corresponding to the source feature, generating a second conversion filter based on a difference between the first spectrum and the second spectrum, and generating target voice by applying the first conversion filter and the second conversion filter to the source spectrum.

Abstract: In voice processing, a first distribution generation unit approximates a distribution of feature information representative of voice of a first speaker per a unit interval thereof as a mixed probability distribution which is a mixture of a plurality of first probability distributions corresponding to a plurality of different phones. A second distribution generation unit also approximates a distribution of feature information representative of voice of a second speaker as a mixed probability distribution which is a mixture of a plurality of second probability distributions. A function generation unit generates, for each phone, a conversion function for converting the feature information of voice of the first speaker to that of the second speaker based on respective statistics of the first and second probability distributions that correspond to the phone.