A voice analysis method, comprising: a variable extraction step of generating a time series of a relative pitch, wherein the relative pitch is a difference between a pitch generated from music track data, which continuously fluctuates on a time axis, and a pitch of a reference voice, wherein the music track data designate respective notes of a music track in time series, wherein the reference voice is a voice obtained by singing the music track, and wherein the pitch of the reference voice is processed by an interpolation processing for a voiceless section from which no pitch is detected; and a characteristics analysis step of generating singing characteristics data that define a model for expressing the time series of the relative pitch generated in the variable extraction step, characterized in that the characteristics analysis step comprises: a section setting step of dividing the music track into a plurality of unit sections by using a predetermined duration as a unit; and an analysis processing step of generating the singing characteristics data, wherein the singing characteristics data includes, for each of a plurality of statuses (St) of the model, classification information and variable information, wherein classification information is for classifying the plurality of unit sections divided by the section setting step into a plurality of sets, wherein variable information defines a probability distribution of the time series of the relative pitch within each of the plurality of unit sections classified into each of the plurality of sets, and wherein the classification information is generated by a first classification processing based on a condition relating to an attribute of the note and by a second classification processing based on the condition relating to an attribute of the each of the plurality of unit sections. a variable extraction step of generating a time series of a relative pitch, wherein the relative pitch is a difference between a pitch generated from music track data, which continuously fluctuates on a time axis, and a pitch of a reference voice, wherein the music track data designate respective notes of a music track in time series, wherein the reference voice is a voice obtained by singing the music track, and wherein the pitch of the reference voice is processed by an interpolation processing for a voiceless section from which no pitch is detected; and a characteristics analysis step of generating singing characteristics data that define a model for expressing the time series of the relative pitch generated in the variable extraction step, a section setting step of dividing the music track into a plurality of unit sections by using a predetermined duration as a unit; and an analysis processing step of generating the singing characteristics data, wherein the singing characteristics data includes, for each of a plurality of statuses (St) of the model, classification information and variable information, wherein classification information is for classifying the plurality of unit sections divided by the section setting step into a plurality of sets, wherein variable information defines a probability distribution of the time series of the relative pitch within each of the plurality of unit sections classified into each of the plurality of sets, and wherein the classification information is generated by a first classification processing based on a condition relating to an attribute of the note and by a second classification processing based on the condition relating to an attribute of the each of the plurality of unit sections.