This paper investigates an end-to-end neural diarization (EEND) method for unknown number of speakers. In contrast to the conventional cascaded approach speaker diarization, EEND methods are better in terms overlap handling. However, still has a disadvantage that it cannot deal with flexible To remedy this problem, we introduce encoder-decoder-based attractor calculation module (EDA) EEND. Once...