The invention provides a method for automated training of a plurality of artificial neural networks for phoneme recognition using training data, wherein the training data comprises speech signals subdivided into frames, each frame associated with a phoneme label, wherein the phoneme label indicates a phoneme associated with the frame, the method comprising the steps of:
providing a sequence of frames from the training data, wherein the number of frames in the sequence of frames is at least equal to the number of artificial neural networks,
assigning to each of the artificial neural networks a different subsequence of the provided sequence, wherein each subsequence comprises a predetermined number of frames,
determining a common phoneme label for the sequence of frames based on the phoneme labels of one or more frames of one or more subsequences of the provided sequence, and
training each artificial neural network using the common phoneme label.