We propose a method of generating a sound which is expected to give a listener a good impression. We aim to use the system to help a robot give a person a good impression in interaction between the robot and the person. In the proposed method, an impression of a sound is estimated based on results of a listener's evaluation to a sound. A spectrogram of a sound is used to learn the relationship between a sound and an evaluation. The evaluation of a sound is estimated based on the spectrogram and not based on the criteria of a sound. Therefore, the proposed method is expected to generate unpredictabile sound. The relationship between the value of an evaluated impression and the data of a sound is estimated by using RNN. We conducted some experiments. It was composed of gathering data of evaluation to some sounds, estimating a listerner's evaluation to sound and generating sounds which was expected to give a listener a good impression.

The large-aperture beam separation dipole (D1 magnet) needs to be developed for the high luminosity upgrade of the Large Hadron Collider (HL-LHC) at CERN. This magnet requires a field integral of 35 T·m at 12.0 kA and 1.9 K with a coil aperture of 150 mm. The technical challenges are controlling the pre-stress of the thin coils, achieving high radiation resistance and managing the iron saturation. In the framework of CERN-KEK collaboration, KEK is in charge of developing the D1 magnet and has been conducting design studies since 2011. A design including a single-layer coil based on Nb-Ti technology with a collared yoke structure was selected and fabrication of the first 2-m model started in 2015. In this paper, the overview and design studies of the D1 magnet are first introduced. Then, fabrication and test results of the first 2-m model are reported. Finally, future perspectives for the D1 production magnets are described.