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Speech emotion recognition (SER) refers to the technique of inferring the emotional state of an individual from speech signals. SERs continue to garner interest due to their wide applicability. While the domain is mainly founded on signal processing, machine learning and deep learning methods, generalizing over languages continues to remain a challenge. To improve performance over languages, in this paper we propose a denoising autoencoder with semi-supervision using a continuous metric loss.doi:10.7557/18.6300 fatcat:na4emlzzhvdy5jfnc6mumbacwi