A speech processing apparatus comprising: an extracting means configured to separate moving image data obtained by imaging a face of a speaker in an utterance period into frames having a predetermined time length, and extract face feature point data indicating positions of face feature points determined in advance, for each frame, wherein face feature points include points on an outline of a face component; a first generating means configured to separate speech data representing uttered speech of the speaker in the utterance period into the frames having a predetermined time length, wherein the speech data has been output from a speech input/output unit; and generate a first generation network for generating face feature points of each frame from speech feature data of the corresponding frame by machine learning; a first evaluating means configured to evaluate whether or not the first generation network is appropriate using the face feature point data extracted from each frame using a first identification network, wherein the first identification network is configured to perform machine learning to distinguish between the face feature point data and the face feature points, and being appropriate means being able to successfully deceive the first identification network; a second generating means configured to cause a user to designate a plurality of types of uncertain settings including at least text representing utterance content of the uttered speech and information indicating emotions included in the uttered speech, cause the user to designate a plurality of types of fixed settings which define speech quality of the speaker, including at least one of gender, age, height, weight, speaking speed, accent of the speaker, and generate a second generation network for generating the uttered speech from the face feature points generated by the first generation network evaluated as appropriate by the first evaluating means, the plurality of types of fixed settings and the plurality of types of uncertain settings designated by the user; and a second evaluating means configured to evaluate the second generation network using a second identification network, wherein the second identification network is configured to evaluate whether or not the second generation network is appropriate using the speech data by machine learning; and a speech synthesizing means configured to synthesize speech corresponding to the fixed settings and the uncertain settings using the second generation network evaluated as appropriate by the second evaluating means. an extracting means configured to separate moving image data obtained by imaging a face of a speaker in an utterance period into frames having a predetermined time length, and extract face feature point data indicating positions of face feature points determined in advance, for each frame, wherein face feature points include points on an outline of a face component; a first generating means configured to separate speech data representing uttered speech of the speaker in the utterance period into the frames having a predetermined time length, wherein the speech data has been output from a speech input/output unit; and generate a first generation network for generating face feature points of each frame from speech feature data of the corresponding frame by machine learning; a first evaluating means configured to evaluate whether or not the first generation network is appropriate using the face feature point data extracted from each frame using a first identification network, wherein the first identification network is configured to perform machine learning to distinguish between the face feature point data and the face feature points, and being appropriate means being able to successfully deceive the first identification network; a second generating means configured to cause a user to designate a plurality of types of uncertain settings including at least text representing utterance content of the uttered speech and information indicating emotions included in the uttered speech, cause the user to designate a plurality of types of fixed settings which define speech quality of the speaker, including at least one of gender, age, height, weight, speaking speed, accent of the speaker, and generate a second generation network for generating the uttered speech from the face feature points generated by the first generation network evaluated as appropriate by the first evaluating means, the plurality of types of fixed settings and the plurality of types of uncertain settings designated by the user; and a second evaluating means configured to evaluate the second generation network using a second identification network, wherein the second identification network is configured to evaluate whether or not the second generation network is appropriate using the speech data by machine learning; and a speech synthesizing means configured to synthesize speech corresponding to the fixed settings and the uncertain settings using the second generation network evaluated as appropriate by the second evaluating means.