Abstract: An autocorrelation calculating part calculates autocorrelation Ro(i) from an input signal. A predictive coefficient calculating part performs linear predictive analysis using modified autocorrelation R?o(i) obtained by multiplying the autocorrelation Ro(i) by a coefficient wo(i). Here, it is assumed that a case where, for at least part of each order i, the coefficient wo(i) corresponding to each order i monotonically increases as a value having negative correlation with a fundamental frequency of an input signal in a current frame or a past frame increases and a case where the coefficient wo(i) monotonically decreases as a value having positive correlation with a pitch gain in a current frame or a past frame increases, are included.

Abstract: A frequency-domain sample interval corresponding to a time-domain pitch period L corresponding to a time-domain pitch period code of an audio signal in a given time period is obtained as a converted interval T1, a frequency-domain pitch period T is chosen from among candidates including the converted interval T1 and integer multiples U×T1 of the converted interval T1, and a frequency-domain pitch period code indicating how many times the frequency-domain pitch period T is greater than the converted interval T1 is obtained. The frequency-domain pitch period code is output so that a decoding side can identify the frequency-domain pitch period T.

Abstract: A frequency-domain sample interval corresponding to a time-domain pitch period L corresponding to a time-domain pitch period code of an audio signal in a given time period is obtained as a converted interval T1, a frequency-domain pitch period T is chosen from among candidates including the converted interval T1 and integer multiples U×T1 of the converted interval T1, and a frequency-domain pitch period code indicating how many times the frequency-domain pitch period T is greater than the converted interval T1 is obtained. The frequency-domain pitch period code is output so that a decoding side can identify the frequency-domain pitch period T.

Abstract: A parameter determination device includes: a spectral envelope estimating portion performing estimation of a spectral envelope using a parameter ?0 specified in a predetermined method, regarding the ?0-th power of absolute values of a frequency domain sample sequence corresponding to a time-series signal as a power spectrum on the assumption that the parameter ?0 and a parameter ? are positive numbers; a whitened spectral sequence generating portion obtaining a whitened spectral sequence which is a sequence obtained by dividing the frequency domain sample sequence by the spectral envelope; and a parameter acquiring portion determining such a parameter ? that generalized Gaussian distribution with the parameter ? as a shape parameter approximates a histogram of the whitened spectral sequence.

Abstract: A technology of accurately coding and decoding coefficients which are convertible into linear prediction coefficients even for a frame in which the spectrum variation is great while suppressing an increase in the code amount as a whole is provided. A coding device includes: a first coding unit that obtains a first code by coding coefficients which are convertible into linear prediction coefficients of more than one order; and a second coding unit that obtains a second code by coding at least quantization errors of the first coding unit if (A-1) an index Q commensurate with how high the peak-to-valley height of a spectral envelope is, the spectral envelope corresponding to the coefficients which are convertible into the linear prediction coefficients of more than one order, is larger than or equal to a predetermined threshold value Th1 and/or (B-1) an index Q? commensurate with how short the peak-to-valley height of the spectral envelope is, is smaller than or equal to a predetermined threshold value Th1?.

Abstract: In encoding, pitch periods for time series signals in a predetermined time interval are calculated, and a code corresponding thereto is output. In that encoding, the resolutions for expressing the pitch periods and/or a pitch period encoding mode are switched according to whether an index indicating a periodicity and/or stationarity level of the time series signals satisfies a condition indicating high or low in periodicity and/or stationarity. In that decoding, according to whether an index indicating a periodicity and/or stationarity level, the index being included in or obtained from an input code corresponding to the predetermined time interval, satisfies a condition indicating high periodicity and/or stationarity, a decoding mode for a code, included in the input code, corresponding to pitch periods is switched to decode the code corresponding to the pitch periods to obtain the pitch periods corresponding to the predetermined time interval.

Abstract: In encoding, pitch periods for time series signals in a predetermined time interval are calculated, and a code corresponding thereto is output. In that encoding, the resolutions for expressing the pitch periods and/or a pitch period encoding mode are switched according to whether an index indicating a periodicity and/or stationarity level of the time series signals satisfies a condition indicating high or low in periodicity and/or stationarity. In that decoding, according to whether an index indicating a periodicity and/or stationarity level, the index being included in or obtained from an input code corresponding to the predetermined time interval, satisfies a condition indicating high periodicity and/or stationarity, a decoding mode for a code, included in the input code, corresponding to pitch periods is switched to decode the code corresponding to the pitch periods to obtain the pitch periods corresponding to the predetermined time interval.

Abstract: In encoding, pitch periods for time series signals in a predetermined time interval are calculated, and a code corresponding thereto is output. In that encoding, the resolutions for expressing the pitch periods and/or a pitch period encoding mode are switched according to whether an index indicating a periodicity and/or stationarity level of the time series signals satisfies a condition indicating high or low in periodicity and/or stationarity. In that decoding, according to whether an index indicating a periodicity and/or stationarity level, the index being included in or obtained from an input code corresponding to the predetermined time interval, satisfies a condition indicating high periodicity and/or stationarity, a decoding mode for a code, included in the input code, corresponding to pitch periods is switched to decode the code corresponding to the pitch periods to obtain the pitch periods corresponding to the predetermined time interval.

Abstract: An autocorrelation calculating part calculates autocorrelation Ro(i) from an input signal. A predictive coefficient calculating part performs linear predictive analysis using modified autocorrelation R?o(i) obtained by multiplying the autocorrelation Ro(i) by a coefficient wo(i). Here, a case is comprised where, for at least part of each order i, the coefficient wo(i) corresponding to each order i monotonically decreases as a value having positive correlation with a pitch gain in an input signal of a current frame or a past frame increases.

Abstract: An autocorrelation calculating part calculates autocorrelation Ro(i) from an input signal. A predictive coefficient calculating part performs linear predictive analysis using modified autocorrelation. R?o(i) obtained by multiplying the autocorrelation Ro(i) by a coefficient wo(i). Here, a case is comprised where, for at least part of each order i, the coefficient wo(i) corresponding to each order i monotonically decreases as a value having positive correlation with a pitch gain in an input signal of a current frame or a past frame increases.

Abstract: An autocorrelation calculating part calculates autocorrelation Ro(i) from an input signal. A predictive coefficient calculating part performs linear predictive analysis using modified autocorrelation R?o(i) obtained by multiplying the autocorrelation Ro(i) by a coefficient wo(i). Here, it is assumed that a case where, for at least part of each order i, the coefficient wo(i) corresponding to each order i monotonically increases as a value having negative correlation with a fundamental frequency of an input signal in a current frame or a past frame increases and a case where the coefficient wo(i) monotonically decreases as a value having positive correlation with a pitch gain in a current frame or a past frame increases, are included.

Abstract: A frequency-domain sample interval corresponding to a time-domain pitch period L corresponding to a time-domain pitch period code of an audio signal in a given time period is obtained as a converted interval T1, a frequency-domain pitch period T is chosen from among candidates including the converted interval T1 and integer multiples U×T1 of the converted interval T1, and a frequency-domain pitch period code indicating how many times the frequency-domain pitch period T is greater than the converted interval T1 is obtained. The frequency-domain pitch period code is output so that a decoding side can identify the frequency-domain pitch period T.

Abstract: A frequency-domain sample interval corresponding to a time-domain pitch period L corresponding to a time-domain pitch period code of an audio signal in a given time period is obtained as a converted interval T1, a frequency-domain pitch period T is chosen from among candidates including the converted interval T1 and integer multiples U×T1 of the converted interval T1, and a frequency-domain pitch period code indicating how many times the frequency-domain pitch period T is greater than the converted interval T1 is obtained. The frequency-domain pitch period code is output so that a decoding side can identify the frequency-domain pitch period T.

Abstract: An autocorrelation calculating part calculates autocorrelation Ro(i) from an input signal. A predictive coefficient calculating part performs linear predictive analysis using modified autocorrelation R?o(i) obtained by multiplying the autocorrelation Ro(i) by a coefficient wo(i). Here, it is assumed that a case where, for at least part of each order i, the coefficient wo(i) corresponding to each order i monotonically increases as a value having negative correlation with a fundamental frequency of an input signal in a current frame or a past frame increases and a case where the coefficient wo(i) monotonically decreases as a value having positive correlation with a pitch gain in a current frame or a past frame increases, are included.

Abstract: An autocorrelation calculating part calculates autocorrelation Ro(i) from an input signal. A predictive coefficient calculating part performs linear predictive analysis using modified autocorrelation R?o(i) obtained by multiplying the autocorrelation Ro(i) by a coefficient wo(i). Here, it is assumed that a case where, for at least part of each order i, the coefficient wo(i) corresponding to each order i monotonically increases as a value having negative correlation with a fundamental frequency of an input signal in a current frame or a past frame increases and a case where the coefficient wo(i) monotonically decreases as a value having positive correlation with a pitch gain in a current frame or a past frame increases, are included.

Abstract: In an encoding method that is expected to produce a smaller code amount out of a periodicity-based encoding method and a non-periodicity-based encoding method, the amount of code or an estimated value of the amount of code of an integer value sequence which is derived from an audio signal is obtained while adjusting gain. In the other encoding method, an integer value sequence obtained in this process is substituted to obtain the amount of code or an estimated value of the amount of code of the integer value sequence. The obtained code amounts or estimated values are compared to choose one of the encoding methods and the integer value sequence is encoded using the chosen encoding method to obtain and output an integer signal code.

Abstract: In an encoding method that is expected to produce a smaller code amount out of a periodicity-based encoding method and a non-periodicity-based encoding method, the amount of code or an estimated value of the amount of code of an integer value sequence which is derived from an audio signal is obtained while adjusting gain. In the other encoding method, an integer value sequence obtained in this process is substituted to obtain the amount of code or an estimated value of the amount of code of the integer value sequence. The obtained code amounts or estimated values are compared to choose one of the encoding methods and the integer value sequence is encoded using the chosen encoding method to obtain and output an integer signal code.

Abstract: An autocorrelation calculating part calculates autocorrelation Ro(i) from an input signal. A predictive coefficient calculating part performs linear predictive analysis using modified autocorrelation R?o(i) obtained by multiplying the autocorrelation Ro(i) by a coefficient wo(i). Here, a case is comprised where, for at least part of each order i, the coefficient wo(i) corresponding to each order i monotonically decreases as a value having positive correlation with a pitch gain in an input signal of a current frame or a past frame increases.

Abstract: A frequency-domain sample interval corresponding to a time-domain pitch period L corresponding to a time-domain pitch period code of an audio signal in a given time period is obtained as a converted interval T1, a frequency-domain pitch period T is chosen from among candidates including the converted interval T1 and integer multiples U×T1 of the converted interval T1, and a frequency-domain pitch period code indicating how many times the frequency-domain pitch period T is greater than the converted interval T1 is obtained. The frequency-domain pitch period code is output so that a decoding side can identify the frequency-domain pitch period T.

Abstract: A linear predictive coding apparatus includes: a linear predictive analysis part performing linear predictive analysis using a pseudo correlation function signal sequence obtained by performing inverse Fourier transform regarding the ?1-th power of absolute values of the frequency domain sample sequence corresponding to the time-series signal as a power spectrum to obtain coefficients transformable to linear predictive coefficients; an adaptation part adapting values ? for a plurality of plural candidates for coefficients transformable to linear predictive coefficients stored in a code book in a code book storing part and the coefficients transformable to linear predictive coefficients obtained by the linear predictive analysis part; and a coding part obtaining a linear predictive coefficient code corresponding to the coefficients transformable to linear predictive coefficients, using the plurality of candidates for coefficients transformable to linear predictive coefficients and the coefficients transformabl