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High performance diarisation is a necessity for a variety of applications, and the task has been
studied extensively in the context of broadcast news and meeting processing. Upon introduction of
the task in NIST led evaluations, diarisation error rate (DER) was introduced as the standard metric
for evaluation, and it has been consistently used to compare systems ever since. DER is a frame
based metric that does not penalise for producing many short segments. However, practical systems

In this paper, automatic speaker verification using normal and whispered speech is explored. Typically, for speaker verification systems with varying vocal effort inputs, standard solutions such as feature mapping or addition of data during parameter estimation (training) and enrollment stages result in a trade-off between accuracy gains with whispered test data and accuracy losses (up to 70% in equal error rate, EER) with normal test data. To overcome this shortcoming, this paper proposes two innovations.