A computer-implemented technique is presented for profiling an unknown speaker. A DNN-based frame selection allows the system to select the relevant frames necessary to provide a reliable speaker characteristic estimation. A frame selection module selects those frames that contain relevant information for estimating a given speaker characteristic and thereby contributes to the accuracy and the low latency of the system. Real-time speaker characteristics estimation allows the system to estimate the speaker characteristics from a speech segment of accumulated selected frames at any given time. The frame level processing contributes to the low latency as it is not necessary to wait for the whole speech utterance to predict a speaker characteristic but rather a speaker characteristic is estimated from only a few reliable frames. Different stopping criteria also contribute to the accuracy and the low latency of the system.
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