  This technical report describes the EML submission to the first VoxCeleb
speaker diarization challenge. Although the aim of the challenge has been the
offline processing of the signals, the submitted system is basically the EML
online algorithm which decides about the speaker labels in runtime
approximately every 1.2 sec. For the first phase of the challenge, only
VoxCeleb2 dev dataset was used for training. The results on the provided
VoxConverse dev set show much better accuracy in terms of both DER and JER
compared to the offline baseline provided in the challenge. The real-time
factor of the whole diarization process is about 0.01 using a single CPU
machine.
