Digital signal processing method, learning method, apparatuses for them, and program storage medium

A digital audio signal processing device for converting a digital audio signal, comprising:

• self correlation coefficient calculation means for cutting parts out of the digital audio signal by plural windows having different sizes;
• means for calculating a self correlation coefficient based on each cut-out part of the digital audio signal;
• means for determining cut-out ranges of time and phase change based on the self correlation coefficient;
• means for compressing the cut-out ranges to form compressed data patterns;
• class-classification means for classifying the compressed data patterns into classes based on the phase changes;
• selection means for selecting a set of prediction coefficients based on the compressed data patterns;
• and
• prediction calculation means for generating a new digital audio signal based upon the prediction coefficients and the cut-out ranges.

A computer memory medium having stored thereon program executed by a digital audio processing device, comprising the steps of:

• a step of cutting parts out of the digital audio signal by plural windows having different sizes;
• a step of calculating a self correlation coefficient for each cut-out part;
• a step of determining cut-out ranges of time and phase changes based on the self correlation coefficients;
• a step of compressing the cut-out ranges to form compressed data patterns:
• a step of classifying the compressed data patterns into classes based on the phase changes;
• a step of selecting a set of prediction coefficients based upon classification of the compressed data patterns;
• and
• a step of generating a new digital audio signal based upon the prediction coefficients and the cut-out ranges.

A learning method for generating prediction coefficients which are used for prediction calculation of conversion processing by a digital signal processing device for converting a digital audio signal, said learning method comprising:

• a step of generating, from a desired digital audio signal, a student digital audio signal in which the digital audio signal is degraded;
• a step of cutting parts out of the student digital audio signal by plural windows having different sizes;
• a step of calculating a self correlation coefficient for each cut-out part,
• a step of determining cut-out ranges of time and phase changes based on the self-correlation coefficients;
• a step of compressing the cut-out ranges to form compressed data patterns;
• a step of classifying the compressed data patterns into classes based on the phase changes;
• a step of calculating prediction coefficients corresponding to the class based on the digital audio signal and the student digital audio signal;
• and
• a step of storing the prediction coefficients associated with each class.

A learning device for generating prediction coefficients which are used for prediction calculation of conversion processing by a digital signal processing device for converting a digital audio signal, said learning device comprising:

• student digital signal processing means for generating, from a desired digital audio signal, a student digital audio signal in which the digital signal is degraded;
• self correlation coefficient calculation means for cutting parts out from the student digital audio signal by multiple windows having different sizes;
• means for calculating a self correlation coefficient for each cut-out part,
• means for determining cut-out ranges of time and phase change based on the self correlation coefficient;
• means for compressing the cut-out ranges to form compressed data patterns;
• class-classification means for classifying the compressed data patterns into classes based on the phase changes;
• prediction coefficient calculation means for calculating prediction coefficients corresponding to the class based on the digital audio signal and the student digital audio signal;
• and
• storage means for storing the prediction coefficients associated with each class.

A computer memory medium having stored thereon program that is executed by a learning device, comprising the steps of:

• a step of generating, from a desired digital audio signal, a student digital audio signal in which the digital audio signal is degraded;
• a step of cutting parts out of the student digital audio signal by plural windows having different sizes;
• a step of calculating a self correlation coefficient for each cut-out part;
• a step of determining cut-out ranges of time and phase changes based on the self-correlation coefficients;
• a step of compressing the cut-out ranges to form compressed data patterns;
• a step of classifying the compressed data patterns into classes based on the phase changes;
• a step of calculating the prediction coefficients corresponding to the class based on the digital audio signal and the student digital audio signal;
• and
• a step of storing the prediction coefficients associated with each class.