(2017) trained a multi-speaker speech recognizer using permutation-free training without explicit objective function for separation.
with our work which uses an end-toend architecture, their objective function relies on a senone posterior probability obtained by aligning unmixed speech and text using a model trained as a recognizer for single-speaker speech.