OpenEAR--introducing the Munich open-source emotion and affect recognition toolkit openEAR is the Munich Open-Source Emotion and Affect Recognition Toolkit developed at the Technische Universität München (TUM). It provides efficient (audio) feature extraction algorithms implemented in C++, classfiers, and pre-trained models on well-k

References in zbMATH (referenced in 2 articles )

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  1. Zhang, Xinran; Tao, Huawei; Zha, Cheng; Xu, Xinzhou; Zhao, Li: A robust method for speech emotion recognition based on infinite Student’s (t)-mixture model (2015)
  2. Mporas, Iosif; Ganchev, Todor: Estimation of unknown speaker’s height from speech (2009) ioport