Abstract: A classification apparatus is configured to perform a classification using a neural network with at least one hidden layer and an output layer, wherein the classification apparatus comprises a coarse training unit configured to train the neural network on a subset of neurons of a last hidden layer and a set of neurons of the output layer; and a fine training unit configured to train the neural network on a set of the last hidden layer and a subset of neurons of the output layer. By executing the classification apparatus, training of a classification model can be improved by reducing the computational burden of the classification, speeding up the training time of a classification model, and speeding up the inference time during application of the classification model.

Abstract: Embodiments of the present disclosure describe a call recording system and a call recording method for automatically recording, i.e. storing, a call candidate when an active call is detected. The call recording system comprises a sound receiver to receive sound data and to convert sound data to audio representations of sound, a buffer to buffer the audio representations of sound for a predetermined time duration, a call candidate determination unit to determine if the buffered audio representations comprise a call candidate, a call analyzer to analyze the call candidate, wherein the call analyzer determines if the call candidate is a call to be stored, and a storage to store the call candidate as a call. Hence, a reliable system can be provided for automatically storing a call.

Abstract: A classification apparatus is configured to perform a classification using a neural network with at least one hidden layer and an output layer, wherein the classification apparatus comprises a coarse training unit configured to train the neural network on a subset of neurons of a last hidden layer and a set of neurons of the output layer; and a fine training unit configured to train the neural network on a set of the last hidden layer and a subset of neurons of the output layer. By executing the classification apparatus, training of a classification model can be improved by reducing the computational burden of the classification, speeding up the training time of a classification model, and speeding up the inference time during application of the classification model.

Abstract: Embodiments of the present disclosure describe a call recording system and a call recording method for automatically recording, i.e. storing, a call candidate when an active call is detected. The call recording system comprises a sound receiver to receive sound data and to convert sound data to audio representations of sound, a buffer to buffer the audio representations of sound for a predetermined time duration, a call candidate determination unit to determine if the buffered audio representations comprise a call candidate, a call analyzer to analyze the call candidate, wherein the call analyzer determines if the call candidate is a call to be stored, and a storage to store the call candidate as a call. Hence, a reliable system can be provided for automatically storing a call.