Dataset Description Dataset Summary TURkish Emotional Speech database (TURES), which includes 5100 utterances extracted from 55 Turkish movies, was constructed. Each utterance in the database is labeled with emotion categories (happy, surprised, sad, angry, fear, neutral and other) and 3- dimensional emotional space (valence, activation, and dominance). • 5100 utterances from 582 (188 female, 394 male) speakers were obtained. The average length of utterances is 2.34 seconds. • The emotion in each utterance was evaluated in a listener test by a large number of annotators (27 university students) independently of one another. Annotators were asked to listen to the entire speech recordings (randomly permuted) and assign an emotion label (both categorical and dimensional) for each utterance. Annotators only took audio information into consideration.

Lago Vista Little League Baseball. For a more thorough explanation of the dataset collection and its contents, see File List The following files are available (each explained in more detail below): File name Part Contents Online self-assessment and emotional class All individual ratings from the online self-assessment and emotional class. Single file for all utterance MFCC, Pitch, LSP, etc. Totally 6552 features (emo_large) For each utterance Pitch (F0) from Esps get_f0 function For each utterance Mel-Frequency Cepstral Coefficients(MFCC) from HTK Speech Recognition Toolkit For each utterance F1,F2, and F3 formants extracted with using Praat File Details •. Ratings The emotion in each utterance was evaluated in a listener test by a large number of annotators (27 university students) independently of one another. • Categorical Annotation Utterances were labelled in seven emotional states: happy, surprised, sad, angry, fear, neutral and other. For each utterance, the final emotion label was computed from the majority label of the 27 annotators. • Annotation in 3D Space For the emotion labelling in 3D space.

CiteSeerX - Document Details (Isaac Councill, Lee Giles, Pradeep Teregowda): Abstract. Thirty-two emotional speech databases are reviewed. Each database consists of a. A Database of German Emotional Speech F. Burkhardt1, A. Paeschke2, M. Sendlmeier2, B. Weiss4 1T-Systems, 2TU Berlin, Department of Communication Science. Emotional Speech Recognition. A total of 87 features has been calculated over 500 utterances from the Danish Emotional Speech database. CiteSeerX - Scientific documents that cite the following paper: Design, recording and verification of a Danish emotional speech database.

Self-Assessment Manikins (SAMs) were used for measuring the emotional content of each audio clip with ratings on a 5 level scale between one and five for valence, activation and dominance. Valence represents negative to positive axis, activation represents calm to excited axis and dominance represents weak to strong axis of 3 dimensional emotion space. For each utterance in the database, annotators were asked to select one of the iconic image from the corresponding row for each of three dimensions.