self-made dataset 2

A non-speech dataset built by a nine-classification discrete emotion model can be used for emotion recognition. The nine emotion dimensions are happy, angry, fearful, sad, brave, favorite, neutral, and calm. Recognition is performed by extracting their 384-dimensional feature vectors, which contain F0 envelopes, short-time excess zero rates, twelve-dimensional Meier cepstral coefficients, etc., as well as their first-order low-pass data. A total of 2,337 data samples were available. All audio files are in wav format and are non-speech files. Each set of audio files is followed by an excel file containing the complete set of 384 dimensional vectors. The author can be contacted if there is anything you need.