update

CHANGELOG.md

@@ -1,6 +1,10 @@
 Changelog
 =========
 
+Version 0.88.11
+--------------
+* removed hack in Praat script 
+
 Version 0.88.10
 --------------
 * SVM C val defaults to 1

nkululeko/constants.py

@@ -1,2 +1,2 @@
-VERSION="0.88.10"
+VERSION="0.88.11"
 SAMPLING_RATE = 16000

nkululeko/feat_extract/feinberg_praat.py

@@ -380,11 +380,11 @@ def compute_features(file_index):
     )
 
     # add pca data
-    pcaData = run_pca(df)  # Run jitter and shimmer PCA
-    df = pd.concat([df, pcaData], axis=1)  # Add PCA data
+    pca_data = run_pca(df)  # Run jitter and shimmer PCA
+    df = pd.concat([df, pca_data], axis=1)  # Add PCA data
     # reload the data so it's all numbers
-    df.to_csv("processed_results.csv", index=False)
-    df = pd.read_csv("processed_results.csv", header=0)
+    # df.to_csv("processed_results.csv", index=False)
+    # df = pd.read_csv("processed_results.csv", header=0)
     #    df.sort_values('voiceID').head(20)
     # ## Next we calculate the vocal-tract length estimates
 

tests/exp_emodb_os_svm.ini

@@ -5,16 +5,15 @@ save = True
 [DATA]
 databases = ['emodb']
 emodb = ./data/emodb/emodb
-emodb.split_strategy = specified
-emodb.test_tables = ['emotion.categories.test.gold_standard']
-emodb.train_tables = ['emotion.categories.train.gold_standard']
+emodb.split_strategy = speaker_split
 target = emotion
-labels = ['anger', 'happiness']
+labels = ['anger', 'boredom', 'disgust', 'fear']
 [FEATS]
-type = os
+type = praat
 scale = standard
 [MODEL]
 type = svm
-tuning_params = ['C']
-scoring = recall_macro
-C = [10, 1, 0.1, 0.01, 0.001, 0.0001]
+#tuning_params = ['C']
+#scoring = recall_macro
+#C = [10, 1, 0.1, 0.01, 0.001, 0.0001]
+[PLOT]