Database containing the results of the analyzed versions of the framework proposed in our paper submitted to the journal Sensors (Basel) under the title "An experimental analysis on multi-cepstral projection representation strategies for dysphonia detection". In this database, we have the following information: "gender": Gender of individuals referring to the selected voice database. For this field, we have the following possible values: “male” for a selection of male individuals, “female” for a selection of female individuals, and “both” for a selection considering both genders. “Techniques”: Concerns about the techniques for extracting cepstral coefficients that we are analyzing. The identifier “nonceps” refers to the use of non-cepstral features. “vowel”: Vowel considered in the database selection. The following values are possible: “a”, “i” and “u”. “intonation”: Tone used by individuals when pronouncing the analyzed vowel. Possible values are: “h” for high; “l” for low; “n” is normal; and “lhl” for low-high-low. “coordinates”: Number of coordinates that make up the feature vector that represents the voice signal after the dimensionality reduction routines. “scale”: Normalization function used on the feature vector. The possible values of this field are the following: “MinMax” for the min-max scale; “Robust” for the robust scale; “Standard” for the standard scale; and “Unscaled” for the unscaled vector. “ACC”: Accuracy obtained by the analyzed version on the considered voice database clipping. “AUC”: Area under the ROC curve obtained by the analyzed version on the considered voice database clipping. “EER”: Equal Error Rate obtained by the analyzed version on the considered voice database clipping. “F1”: F1-score obtained by the analyzed version on the considered voice database clipping. “EH”: Rate of healthy voice signals classified as pathological on the considered voice database clipping. “EP”: Rate of pathological voice signals classified as healthy on the considered voice database clipping. “KFCV”: Average accuracy score of a 5-fold Cross Validation over the training dataset on the considered voice database clipping. “Balancing”: Indication of the use of balancing technique (SMOTE) by the considered framework version. “Classifier”: Classifier used, being possible the use of Random Forest (RF), Logistic Regression (LR), and Support Vector Machine (SVM). “Multi-Projection”: Multi-projection strategies employed by the evaluated technique. “Features”: Type of feature that defines the feature vector. In this case, the following values are possible in this field: “NonCeps” for non-cepstral features; “Ceps” for cepstral features only; and “Ceps and NonCeps” for features of cepstral and non-cepstral types. . It is worth noting that the symbol “-”, present in some fields, represents the “non-use” of any technique of the type indicated by the field. For example, in the case of the “Balancing” field, the value “-” means that no data balancing technique was used in the evaluated version of the framework.