Abstract: An information processing system includes at least one memory storing a program and at least one processor. The at least one processor implements the program to input a piece of sound source data obtained by encoding a first identification data representative of a sound source, a piece of style data obtained by encoding a second identification data representative of a performance style, and synthesis data representative of sounding conditions into a synthesis model generated by machine learning, and to generate, using the synthesis model, feature data representative of acoustic features of a target sound of the sound source to be generated in the performance style and according to the sounding conditions, and to generate an audio signal corresponding to the target sound using the generated feature data.

Abstract: A sound processing method obtains note data representative of a note; obtains an audio signal to be processed; specifies, in accordance with the note, an expression sample representative of a sound expression to be imparted to the note and an expression period, of the audio signal, to which the sound expression is to be imparted to the note; and specifies, in accordance with the expression sample and the expression period, a processing parameter relating to an expression imparting processing for imparting the sound expression to a portion corresponding to the expression period in the audio signal. The method then generates a processed audio signal by performing the expression imparting processing in accordance with the expression sample, the expression period, and the processing parameter to the audio signal.

Abstract: A computer-implemented sound signal generation method includes: obtaining a first sound source spectrum of a sound signal to be generated; obtaining a first spectral envelope of the sound signal; and estimating fragment data representative of samples of the sound signal based on the obtained first sound source spectrum and the obtained first spectral envelope.

Abstract: A voice synthesis method according to an embodiment includes altering a series of synthesis spectra in a partial period of a synthesis voice based on a series of amplitude spectrum envelope contours of a voice expression to obtain a series of altered spectra to which the voice expression has been imparted, and synthesizing a series of voice samples to which the voice expression has been imparted, based on the series of altered spectra.

Abstract: A voice synthesis method includes: sequentially acquiring voice units comprising at least one of diphone or a triphone in accordance with synthesis information for synthesizing voices; generating statistical spectral envelopes using a statistical model built by machine learning in accordance with the synthesis information for synthesizing the voices; and concatenating the sequentially acquired voice units and modifying a frequency spectral envelope of each voice unit in accordance with the generated statistical spectral envelope, thereby synthesizing a voice signal based on the concatenated voice units having the modified frequency spectra.

Abstract: A computer-implemented sound signal generation method includes: obtaining a first sound source spectrum of a sound signal to be generated; obtaining a first spectral envelope of the sound signal; and estimating fragment data representative of samples of the sound signal based on the obtained first sound source spectrum and the obtained first spectral envelope.

Abstract: A computer-implemented sound signal synthesis method includes: generating, based on first control data representative of a plurality of conditions of a sound signal to be generated, (i) first data representative of a sound source spectrum of the sound signal, and (ii) second data representative of a spectral envelope of the sound signal; and synthesizing the sound signal based on the sound source spectrum indicated by the first data and the spectral envelope indicated by the second data.

Abstract: An information processing system includes at least one memory storing a program and at least one processor. The at least one processor implements the program to input a piece of sound source data representative of a sound source, a piece of style data representative of a performance style, and synthesis data representative of sounding conditions into a synthesis model generated by machine learning, and to generate, using the synthesis model, feature data representative of acoustic features of a target sound of the sound source to be generated in the performance style and according to the sounding conditions, and to generate an audio signal corresponding to the target sound using the generated feature data.

Abstract: A sound processing method obtains note data representative of a note; obtains an audio signal to be processed; specifies, in accordance with the note, an expression sample representative of a sound expression to be imparted to the note and an expression period, of the audio signal, to which the sound expression is to be imparted to the note; and specifies, in accordance with the expression sample and the expression period, a processing parameter relating to an expression imparting processing for imparting the sound expression to a portion corresponding to the expression period in the audio signal. The method then generates a processed audio signal by performing the expression imparting processing in accordance with the expression sample, the expression period, and the processing parameter to the audio signal.

Abstract: A voice synthesis method according to an embodiment includes altering a series of synthesis spectra in a partial period of a synthesis voice based on a series of amplitude spectrum envelope contours of a voice expression to obtain a series of altered spectra to which the voice expression has been imparted, and synthesizing a series of voice samples to which the voice expression has been imparted, based on the series of altered spectra.

Abstract: A voice synthesis method includes: sequentially acquiring voice units in accordance with synthesis information for synthesizing voices; generating statistical spectral envelopes using a statistical model in accordance with the synthesis information for synthesizing the voices; and concatenating the sequentially acquired voice units and modifying a frequency spectral envelope of each voice unit in accordance with the generated statistical spectral envelope, thereby synthesizing a voice signal based on the concatenated voice units having the modified frequency spectra.

Abstract: A voice synthesis method for generating a voice signal through connection of a phonetic piece extracted from a reference voice, includes selecting, by a piece selection unit, the phonetic piece sequentially; setting, by a pitch setting unit, a pitch transition in which a fluctuation of an observed pitch of the phonetic piece is reflected based on a degree corresponding to a difference value between a reference pitch being a reference of sound generation of the reference voice and the observed pitch of the phonetic piece selected by the piece selection unit; and generating, by a voice synthesis unit, the voice signal by adjusting a pitch of the phonetic piece selected by the piece selection unit based on the pitch transition generated by the pitch setting unit.

Abstract: A processing unit of a voice processing apparatus first generates a target voice signal in a time domain by adjusting a fundamental frequency of a target voice signal to a fundamental frequency of an initial voice signal, so as to generate a spectrum of the target voice signal after pitch is adjusted. Second, the processing unit reallocates, along a frequency axis, the spectrum of the target voice characteristics by having the spectrum correspond to each of the fundamental frequencies of the initial voice signal.

Abstract: A voice synthesis method for generating a voice signal through connection of a phonetic piece extracted from a reference voice, includes selecting, by a piece selection unit, the phonetic piece sequentially; setting, by a pitch setting unit, a pitch transition in which a fluctuation of an observed pitch of the phonetic piece is reflected based on a degree corresponding to a difference value between a reference pitch being a reference of sound generation of the reference voice and the observed pitch of the phonetic piece selected by the piece selection unit; and generating, by a voice synthesis unit, the voice signal by adjusting a pitch of the phonetic piece selected by the piece selection unit based on the pitch transition generated by the pitch setting unit.

Abstract: A processing unit of a voice processing apparatus first generates a target voice signal in a time domain by adjusting a fundamental frequency of a target voice signal to a fundamental frequency of an initial voice signal, so as to generate a spectrum of the target voice signal after pitch is adjusted. Second, the processing unit reallocates, along a frequency axis, the spectrum of the target voice characteristics by having the spectrum correspond to each of the fundamental frequencies of the initial voice signal.

Abstract: In a voice processing apparatus, a processor is configured to adjust, a fundamental frequency of a first voice signal corresponding to a voice having target voice characteristics to a fundamental frequency of a second voice signal corresponding to a voice having initial voice characteristics different from the target voice characteristics. The processor is further configured to sequentially generate a processed spectrum based on a spectrum of the first voice signal and a spectrum of the second voice signal by: dividing the spectrum of the first voice signal into a plurality of harmonic band components after the fundamental frequency of the first voice signal has been adjusted; allocating each harmonic band component of the first voice signal to each harmonic frequency associated with the fundamental frequency of the second voice signal; and adjusting an envelope and phase of each harmonic band component according to the spectrum of the second voice signal.

Abstract: Candidate frequencies per unit segment of an audio signal are identified. First processing section identifies an estimated train that is a time series of candidate frequencies, each selected for a different one of the segments, arranged over a plurality of the unit segments and that has a high likelihood of corresponding to a time series of fundamental frequencies of a target component. Second processing section identifies a state train of states, each indicative of one of sound-generating and non-sound-generating states of the target component in a different one of the segments, arranged over the unit segments. Frequency information which designates, as a fundamental frequency of the target component, a candidate frequency corresponding to the unit segment in the estimated train is generated for each unit segment corresponding to the sound-generating state. Frequency information indicative of no sound generation is generated for each unit segment corresponding to the non-sound-generating state.

Abstract: A coefficient train processing section, which sequentially generates per unit segment a processing coefficient train for suppressing a target component of an audio signal, includes a basic coefficient train generation section and coefficient train processing section. The basic coefficient train generation section generates a basic coefficient train where basic coefficient values corresponding to frequencies within a particular frequency band range are each set at a suppression value that suppresses the audio signal while coefficient values corresponding to frequencies outside the particular frequency band range are each set at a pass value that maintains the audio signal. The coefficient train processing section generates the processing coefficient train, per unit segment, by changing, to the pass value, each of the coefficient values corresponding to frequencies other than the target component among the coefficient values corresponding to the frequencies within the particular frequency band range.

Abstract: Signal processing section of a terminal converts acquired audio signals of a plurality of channels into frequency spectra set, calculates sound image positions corresponding to individual frequency components, and displays, on a display screen, the calculated sound image positions results by use of a coordinate system having coordinate axes of the frequency components and sound image positions. User-designated partial region of the coordinate system is set as a designated region and an amplitude-level adjusting amount is set for the designated region, so that the signal processing section adjusts amplitude levels of frequency components included in the frequency spectra and in the designated region, converts the adjusted frequency components into audio signals and outputs the converted audio signals.

Abstract: In a voice synthesis apparatus, a phoneme piece interpolator acquires first phoneme piece data corresponding to a first value of sound characteristic, and second phoneme piece data corresponding to a second value of the sound characteristic. The first and second phoneme piece data indicate a spectrum of each frame of a phoneme piece. The phoneme piece interpolator interpolates between each frame of the first phoneme piece data and each frame of the second phoneme piece data so as to create phoneme piece data of the phoneme piece corresponding to a target value of the sound characteristic which is different from either of the first and second values of the sound characteristic. A voice synthesizer generates a voice signal having the target value of the sound characteristic based on the created phoneme piece data.