Method of transforming periodic signal using smoothed spectrogram, method of transforming sound using phasing component and method of analyzing signal using optimum interpolation function

• US 6,115,684 A
• Filed: 07/29/1997
• Issued: 09/05/2000
• Est. Priority Date: 07/30/1996
• Status: Expired due to Term

• Current Assignee: Advanced Telecommunications Research Institute International
• Original Assignee: ATR Human Information Processing Research Laboratories
• Inventors: Kawahara, Hideki, Masuda, Ikuyo
• Primary Examiner(s): Zele, Krista
• Assistant Examiner(s): Opsasnick, Michael N.
• Application Number:
  US08/902,546
• Time in Patent Office: 1,134 Days
• Field of Search: 704/200, 704/201, 704/203, 704/204, 704/205, 704/211
• US Class Current: 704/203
• CPC Class Codes: G10L 2021/0135 Voice conversion or morphing
• CPC Class Codes: G10L 21/04 Time compression or expansion
• CPC Class Codes: G10L 25/48 specially adapted for particular use

Abstract

At a smoothing spectrogram calculation portion, a triangular interpolation function having a frequency width twice that of the fundamental frequency of a signal is obtained based on information on the fundamental frequency of the signal. The interpolation function and a spectrum obtained at an adaptive frequency analysis portion are convoluted in the direction of frequency. Then, using a triangular interpolation function having a time length twice that of a fundamental period, the spectrum interpolated in the frequency direction described above is further interpolated in the temporal direction, in order to produce a smoothed spectrogram having the space between grid points on the time-frequency plane filled with the surface of a bilinear function. Using the smoothed spectrogram, a speech sound is transformed. Therefore, the influence of periodicity in the frequency direction and the temporal direction can be reduced.

Claims

1. A method of synthesizing a sound,

producing an impulse response, based on the product of a phasing component and a spectrum of a source sound, wherein a sound source signal resulting from the phasing component has a power spectrum the same as the impulse and energy distributed in time;

and

synthesizing said sound from said source sound by adding up said impulse response while moving said response by a period of interest on the temporal axis;

wherein;

said phasing component is a product of a first component and a second component,

said first component Φ

(ω

) is represented as follows;

##EQU18## wherein exp ( ) represents an exponential function, ω

represents an angular frequency, ξ

(ω

) represents a continuous odd function, Λ

represents a set of a finite number of numerals, k represents a single numeral extracted from Λ

, α

_k represents a factor, m_k represents a parameter, and ρ

(ω

) represents a function indicating a weight, and

said second component is produced by the steps of;

obtaining a band-limited random number by convoluting a random number and a band-liming function on the frequency axis;

obtaining a group delay characteristic by multiplying said band-limited random number and a target value for fluctuation of delay time;

obtaining a phase characteristic by integrating said group delay characteristic by a frequency; and

multiplying said phase characteristic by an imaginary number unit to produce the exponent of a exponential function.

2. A method of synthesizing a sound, comprising the steps of:

producing an impulse response, based on the product of a phasing component and a spectrum of a source sound, wherein a sound source signal resulting from the phasing component has a power spectrum the same as the impulse and energy distributed in time; and

synthesizing said sound from said source sound by adding up said impulse response while moving said response by a period of interest on the temporal axis;

wherein said phasing component is obtained by the steps of;

obtaining a band-limited random number by convoluting a random number and a band-limiting function on the frequency axis;

obtaining a group delay characteristic by multiplying said band-limited random number and a target value for fluctuation of delay time;

obtaining a phase characteristic by integrating said group delay characteristic by a frequency; and

multiplying said phase characteristic and an imaginary number unit to produce the exponent of an exponential function.

3. A method of synthesizing a sound, comprising the steps of:

producing an impulse response, based on the product of a phasing component and a spectrum of a source sound, wherein a sound source signal resulting from the phasing component has a power spectrum the same as the impulse and energy distributed in time; and

synthesizing said sound from said source sound by adding up said impulse response while moving said response by a period of interest on the temporal axis;

wherein said phasing component is represented as Φ

(ω

) in the following equation;

##EQU19## wherein exp ( ) represents an exponential function, ω

represents an angular frequency, ξ

(ω

) represents a continuous odd function, Λ

represents a set of a finite number of numerals, k represents a single numeral extracted from Λ

, α

_k represents a factor, m_k represents a parameter and ρ

(ω

) represents a function indicating a weight.

4. A method of signal analysis, comprising the steps of:

sampling and digitizing a nearly periodic signal;

hypothesizing a time frequency surface representing the sampled, digitized nearly periodic signal, said time frequency surface represented as a product of a piecewise polynomial of time and a piecewise polynomial of frequency;

extracting a prescribed range of said nearly periodic signal using a window function;

producing a first spectrum from said nearly periodic signal in said extracted prescribed range;

producing an optimum interpolation function in the direction of frequency from a representation in the frequency region of said window function and the basis of a space represented by said piecewise polynomial of frequency; and

producing a second spectrum by convoluting said first spectrum and said optimal interpolation function in the direction of frequency, wherein

said optimum interpolation function in the direction of frequency minimizes an error between said second spectrum and a section along the frequency axis of said time frequency surface.

5. The signal analysis method of claim 4, further comprising transforming said second spectrum into a third spectrum, using a monotonic smoothed function which maps the region of -∞

to +∞

to the region of 0 to +∞

.

8. A signal analysis method of claim 4, further comprising the steps of:

producing a plurality of said second spectra at each arbitrary time;

transferring said plurality of second spectra to a plurality of third spectra, using a first monotonic smoothed function which maps the region of -∞

to +∞

to the region of 0 to +∞

;

producing a first spectrogram by arranging said plurality of third spectra in the direction of time;

producing an optimum interpolation function in the direction of time from a representation of said window function in a time region and the basis of a space represented in said piecewise polynomial of time;

producing a second spectrogram by convoluting said first spectrogram and said optimum interpolation function in the direction of time; and

transforming said second spectrogram into a third spectrogram, using a second monotonic smoothed function which maps the region of -∞

to +∞

to the region of 0 to +∞

, wherein

said optimum interpolation function in the direction of time minimizes an error between said second spectrogram and said time frequency surface.

6. A signal analysis method comprising the steps of:

sampling and digitizing a nearly periodic signal;

hypothesizing a time frequency surface representing the sampled, digitized nearly periodic signal, said time frequency surface represented as a product of a piecewise polynomial of time and a piecewise polynomial of frequency;

extracting a prescribed range of said nearly periodic signal using a window function;

producing a first spectrum from said nearly periodic signal in said extracted prescribed range;

producing an optimum interpolation function in the direction of frequency from a representation in the frequency region of said window function and the basis of a space represented by said piecewise polynomial of frequency;

producing a fourth spectrum by removing the influence of the fundamental frequency of said nearly periodic signal from said first spectrum;

producing a fifth spectrum by dividing said first spectrum by said fourth spectrum;

producing a second spectrum by convoluting said fifth spectrum and said optimal interpolation function in the direction of frequency;

transforming said second spectrum into a third spectrum, using a monotonic smoothed function which maps the region of -∞

to +∞

to the region of 0 to +∞

; and

producing a sixth spectrum by multiplying said third spectrum by said fourth spectrum, wherein

said optimum interpolation function in the direction of frequency minimizes an error between said second spectrum and a section along the frequency axis of said time freguency surface.

7. A signal analysis method comprising the steps of:

producing an optimum interpolation function in the direction of time from a representation of said window function in a time region and the basis of a space represented in said piecewise polynomial of time;

producing a plurality of said second spectra at every arbitrary time;

producing a first spectrogram by arranging said plurality of second spectra in the direction of time;

producing a second spectrogram by convoluting said first spectrogram and said optimum interpolation function in the direction of time, wherein

said optimum interpolation function in the direction of time minimizes an error between said second spectrogram and said time frequency surface.

9. A signal analysis method comprising the steps of:

sampling and digitizing a nearly periodic signal;

hypothesizing a time frequency surface representing the sampled, digitized nearly periodic signal, said time frequency surface represented as a product of a piecewise polynomial of time and a piecewise polynomial of frequency;

extracting a prescribed range of said nearly periodic signal, using a window function;

producing a first spectrum from said nearly periodic signal in said extracted prescribed range;

producing a plurality of said first spectra at each arbitrary time;

producing a plurality of second spectra by removing the influence of the fundamental frequency of said nearly periodic signal from said plurality of first spectra;

producing a plurality of third spectra by dividing said each first spectrum by a corresponding one of said second spectra;

producing an optimum interpolation function in the direction of frequency from a representation of said window function in a frequency region and the basis of a space represented by said piecewise polynomial of said frequency;

producing a plurality of fourth spectra by convoluting each said third spectra and said optimum interpolation function in the direction of frequency;

transforming said plurality of fourth spectra into a plurality of fifth spectra, using a first monotonic smoothed function which maps the region of -∞

to +∞

to the region of 0 to +∞

;

producing a plurality of sixth spectra by multiplying each said fifth spectra and a corresponding one of said second spectra;

producing a first spectrogram by arranging said plurality of sixth spectra in the direction of time;

producing a second spectrogram by removing the influence of temporal fluctuation based on the periodicity of said nearly periodic signal from said first spectrogram;

producing a third spectrogram by dividing said first spectrogram by said second spectrogram;

producing an optimum interpolation function in the direction of time from a representation of said window function in a time region and the basis of a space represented in said piecewise polynomial of time;

producing a fourth spectrogram by convoluting said third spectrogram and said optimum interpolation function in the direction of time;

transforming said fourth spectrogram into a fifth spectrogram, using a second monotonic smoothed function which maps the region of -∞

to +∞

to the region of 0 to +∞

; and

producing a sixth spectrogram by multiplying said fifth spectrogram by said second spectrogram, wherein

said optimum interpolation function in the direction of time minimizes an error between said fourth spectrum and a section along the frequency axis of said time frequency surface, and

said optimum interpolation function in the direction of time minimizes an error between said fourth spectrogram and said time frequency surface.

10. A signal analysis method, comprising the steps of:

sampling and digitizing a nearly periodic signal;

producing a first spectrum of the sampled, digitized nearly periodic signal whose characteristic changes with time, using a first window function;

producing a second window function, using a prescribed window function;

producing a second spectrum of said nearly periodic signal, using said second window function; and

producing an average value of said first spectrum and said second spectrum through transformation by square or a monotonic non-negative function, and making a resultant average value a third spectrum, wherein

said step of producing said second window function includes the step of;

positioning said prescribed window functions apart at an interval of a fundamental period on both sides of the origin;

inverting the sign of one of said positioned prescribed window functions; and

producing said second window function by combining said sign-inverted prescribed window function and said the other prescribed window function.

11. The signal analysis method of claim 10, further comprising the steps of:

producing a plurality of said third spectra at each arbitrary time; and

producing a spectrogram by arranging said plurality of third spectra in the direction of time.