Before revision:  We further compare both CNN and multi-head self-attention to compute the speaker turn embeddings and show that in low-resource situations, the best results are obtained by combining all sources of transferred information  .
After revision:  We further compare both CNN and multi-head self-attention to compute the speaker turn embeddings and show that in low-resource situations, the best results are obtained by combining all sources of transferred information . We further demonstrate that the proposed methods significantly outperform related cross-lingual DA recognition approaches .