Yamaha Corporation

Keijiro Saino

Jordi Bonada

Merlijn Blaauw

Ryunosuke Daido

Yuji Hisaminato

Michael Wilson

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.

Voice synthesis method, voice synthesis device, and storage medium

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.

Voice synthesis apparatus and voice synthesis method utilizing diphones or triphones and machine learning

A display control method executed by a processor, the method includes the steps of: displaying, on a display device, a note icon that represents a note of a voice to be synthesized and an indicator that is moved in accordance with an operation received from a user; displaying, on the display device, first options that belong to a first layer among layers in a hierarchical structure, for the user to select a singing expression to be applied to the note from among a plurality of singing expressions; and displaying, on the display device, when the indicator is moved into an area corresponding to a particular option selected from among the first options, second options that correspond to the particular option and belong to a second layer that is below the first layer in the hierarchical structure.

Display control method and editing apparatus for voice synthesis

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.

Voice synthesis method, voice synthesis device, medium for storing voice synthesis program

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. The processing unit then generates a converted spectrum by adjusting component values of the spectrum of the target voice characteristics, which spectrum has been reallocated, so as to correspond to the component values of the spectrum of the initial voice signal, and by adapting the component values of the spectrum of the initial voice signal to specific frequency bands of the spectrum of the target voice characteristics, with each specific frequency band including one of the harmonic frequencies corresponding to the fundamental frequency of the initial voice signal.

Voice processing method and apparatus, and recording medium therefor

A voice signal is synthesized using a plurality of phonetic piece data each indicating a phonetic piece containing at least two phoneme sections corresponding to different phonemes. In the apparatus, a phonetic piece adjustor forms a target section from first and second phonetic pieces so as to connect the first and second phonetic pieces to each other such that the target section includes a rear phoneme section of the first piece and a front phoneme section of the second piece, and expands the target section by a target time length to form an adjustment section such that a central part is expanded at an expansion rate higher than that of front and rear parts of the target section, to thereby create synthesized phonetic piece data having the target time length. A voice synthesizer creates a voice signal from the synthesized phonetic piece data.

Voice synthesis apparatus using a plurality of phonetic piece data

For each one note or for each plurality of notes constituting a reference tone, a segment setting section segments a time series of actual pitches of the reference tone into one or more note segments. For each of the one or more note segments, a relativization section creates a time series of relative pitches that are relative values of individual ones of the actual pitches of the reference tone to a normal pitch of the note of the note segment. Information registration section stores, into a storage device, relative pitch information comprising the time series of relative pitches of each individual one of the note segments. The segment setting section may use musical score data, time-serially designating the notes of the reference tone, to set each of the note segments for each note designated by the musical score data, and may correct at least one of start and end points of each of the set note segments in response to user's operation.

Tone synthesizing data generation apparatus and method

Phase setting section sets virtual phases in a frequency series of an audio signal. Unit wave extraction section extracts, from the frequency series, a unit wave of one cyclic period defined by the set virtual phases, for each of a plurality of time points. First generation section generates velocity information corresponding to a degree of compression/expansion, to a predetermined length, of the unit wave. Second generation section generates shape information indicative of a shape of a frequency spectrum of the unit wave having been adjusted. Variation component impartment section generates a variation component by use of the velocity information and shape information generated for the individual time points.

Audio processing apparatus and method

Variation over time in fundamental frequency in singing voices is separated into a melody-dependent component and a phoneme-dependent component, modeled for each of the components and stored into a singing synthesizing database. In execution of singing synthesis, a pitch curve indicative of variation over time in fundamental frequency of the melody is synthesized in accordance with an arrangement of notes represented by a singing synthesizing score and the melody-dependent component, and the pitch curve is corrected, for each of pitch curve sections corresponding to phonemes constituting lyrics, using a phoneme-dependent component model corresponding to the phoneme. Such arrangements can accurately model a singing expression, unique to a singing person and appearing in a melody singing style of the person, while taking into account phoneme-dependent pitch variation, and thereby permits synthesis of singing voices that sound more natural.

Apparatus and method for creating singing synthesizing database, and pitch curve generation apparatus and method

Waveform data representative of singing voices of a singing music piece are analyzed to generate melody component data representative of variation over time in fundamental frequency component presumed to represent a melody in the singing voices. Then, through machine learning that uses score data representative of a musical score of the singing music piece and the melody component data, a melody component model, representative of a variation component presumed to represent the melody among the variation over time in fundamental frequency component, is generated for each combination of notes. Parameters defining the melody component models and note identifiers indicative of the combinations of notes whose variation over time in fundamental frequency component are represented by the melody component models are stored into a pitch curve generating database in association with each other.

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Hamamatsu, Japan

Keijiro Saino