Method, apparatus, and program for assessing similarity of performance sound
First Claim
1. A similarity assessment method of a performance sound, comprising:
- a probability density function generating process of dividing one performance sound into a sequence of frames each having a predetermined temporal length and also dividing another performance sound to be compared with said one performance sound into another sequence of frames each having the predetermined temporal length, and generating a probability density function of a fundamental frequency for each frame of the respective performance sounds; and
a similarity assessment process of comparing the probability density function of a frame of said one performance sound with the probability density function of a frame of said another performance sound so as to assess a similarity between said one performance sound and said another performance sound, whereinthe probability density function generating process uses a plurality of tone models which simulate various harmonic structures of sounds generated from a musical instrument and defines a weighted mixture of the tone models corresponding to various fundamental frequencies, and recurrently updates and optimizes respective weight values of the tone models so that a frequency distribution of the weighted mixture of the tone models represents frequency components of the performance sound, thereby outputting the optimized weight values as the probability density function of the fundamental frequency of the performance sound.
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Abstract
A similarity assessment apparatus is provided for assessing a performance sound based on a model performance sound. In the apparatus, a probability density function generating unit divides data of a performance sound into a sequence of frames each having a predetermined temporal length, and generates a probability density function of a fundamental frequency for each frame of the performance sound. A probability density function providing portion provides a probability density function of a fundamental frequency for each frame of the model performance sound. A similarity assessment unit compares the generated probability density function of a frame of the performance sound with the provided probability density function of a frame of the model performance sound so as to assess a similarity between the performance sound and the model performance sound.
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Citations
8 Claims
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1. A similarity assessment method of a performance sound, comprising:
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a probability density function generating process of dividing one performance sound into a sequence of frames each having a predetermined temporal length and also dividing another performance sound to be compared with said one performance sound into another sequence of frames each having the predetermined temporal length, and generating a probability density function of a fundamental frequency for each frame of the respective performance sounds; and a similarity assessment process of comparing the probability density function of a frame of said one performance sound with the probability density function of a frame of said another performance sound so as to assess a similarity between said one performance sound and said another performance sound, wherein the probability density function generating process uses a plurality of tone models which simulate various harmonic structures of sounds generated from a musical instrument and defines a weighted mixture of the tone models corresponding to various fundamental frequencies, and recurrently updates and optimizes respective weight values of the tone models so that a frequency distribution of the weighted mixture of the tone models represents frequency components of the performance sound, thereby outputting the optimized weight values as the probability density function of the fundamental frequency of the performance sound.
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2. A similarity assessment apparatus for assessing a performance sound based on a model performance sound, comprising:
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a probability density function generating unit that divides data of a performance sound into a sequence of frames each having a predetermined temporal length, and generates a probability density function of a fundamental frequency for each frame of the performance sound, wherein the probability density function generating unit uses a plurality of tone models which simulate various harmonic structures of sounds generated from a musical instrument and defines a weighted mixture of the tone models corresponding to various fundamental frequencies, and recurrently updates and optimizes respective weight values of the tone models so that a frequency distribution of the weighted mixture of the tone models represents frequency components of the performance sound, thereby outputting the optimized weight values as the probability density function of the fundamental frequency of the performance sound; a probability density function providing portion that provides a probability density function of a fundamental frequency for each frame of the model performance sound; and a similarity assessment unit that compares the generated probability density function of a frame of the performance sound with the provided probability density function of a frame of the model performance sound so as to assess a similarity between the performance sound and the model performance sound. - View Dependent Claims (3, 4, 5, 6, 7)
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8. A machine readable medium for use in a computer, the medium containing program instructions executable by the computer to perform processes of assessing a performance sound based on a model performance sound, wherein the processes comprise:
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a probability density function generating process of dividing data of a performance sound into a sequence of frames each having a predetermined temporal length, and generating a probability density function of a fundamental frequency for each frame of the performance sound, wherein the probability density function generating process uses a plurality of tone models which simulate various harmonic structures of sounds generated from a musical instrument and defines a weighted mixture of the tone models corresponding to various fundamental frequencies, and recurrently updates and optimizes respective weight values of the tone models so that a frequency distribution of the weighted mixture of the tone models represents frequency components of the performance sound, thereby outputting the optimized weight values as the probability density function of the fundamental frequency of the performance sound; a probability density function acquiring process of acquiring a probability density function of a fundamental frequency for each frame of the model performance sound; and a similarity assessment process of comparing the generated probability density function of a frame of the performance sound with the acquired probability density function of a frame of the model performance sound so as to assess a similarity between the performance sound and the model performance sound.
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Specification