update

1.3.0/create.py

@@ -52,33 +52,53 @@ def main():
     df = df[df["corrupted"] != True]
     audeer.mkdir(image_dir)
     util.describe_df(df, f"{image_dir}all.png")
+    # make a dataframe for 20 samples per speaker
+    df_lim = util.limit_speakers(df)
+    util.describe_df(df_lim, f"{image_dir}limited.png")
+    # make a dataframe for emotionally neutral samples
     df["emotion"] = df_emo["emotion.0"].values
-    df = df[df.emotion.isin(["neutral"])]
-    util.describe_df(df, f"{image_dir}all_neutral.png")
-    df = util.limit_speakers(df)
-    util.describe_df(df, f"{image_dir}all_limited.png")
+    df_neut = df[df.emotion.isin(["neutral"])]
+    util.describe_df(df_neut, f"{image_dir}neutral.png")
+    # make a dataframe for emotionally neutral samples , limited to 20 samples
+    df_neut_lim = util.limit_speakers(df_neut)
+    util.describe_df(df_neut_lim, f"{image_dir}neutral_limited.png")
 
-    # create split sets
-    splits = {}
-    df_train, df_dev, df_test = trainDevTestSplit.split_df(df)
-    splits["train"] = df_train
-    splits["dev"] = df_dev
-    splits["test"] = df_test
+    # create split sets for samples from all emotions
+    splits_emo = {}
+    df_train, df_dev, df_test = trainDevTestSplit.split_df(df_lim)
+    splits_emo["train"] = df_train
+    splits_emo["dev"] = df_dev
+    splits_emo["test"] = df_test
+    # create split sets for neutral samples
+    splits_neut = {}
+    df_train, df_dev, df_test = trainDevTestSplit.split_df(df_neut_lim)
+    splits_neut["train"] = df_train
+    splits_neut["dev"] = df_dev
+    splits_neut["test"] = df_test
     # plot distributions
-    for split in ["train", "dev", "test"]:
+    for split in splits_emo.keys():
         print(f"split: {split}")
-        util.describe_df(splits[split], f"{image_dir}{split}.png")
+        util.describe_df(splits_emo[split], f"{image_dir}{split}.png")
+        util.describe_df(splits_neut[split], f"{image_dir}{split}_neut.png")
 
     # fill the database with new tables
     age_tables_name = "age."
-    for split in splits.keys():
+    age_tables_emotional_name = "age.emotional."
+    for split in splits_emo.keys():
         db[f"{age_tables_name}{split}"] = audformat.Table(
-            splits[split].index,
-            description=f"Table selected for age and binary gender balance from the emotionally neutral samples, max 20 samples per speaker.",
+            splits_neut[split].index,
+            description=f"Table selected for age and binary gender balance from the emotionally neutral samples,  limited to 20 samples per speaker.",
         )
         for field in ["speaker"]:
             db[f"{age_tables_name}{split}"][field] = audformat.Column(scheme_id=field)
-            db[f"{age_tables_name}{split}"][field].set(splits[split][field])
+            db[f"{age_tables_name}{split}"][field].set(splits_neut[split][field])
+        db[f"{age_tables_emotional_name}{split}"] = audformat.Table(
+            splits_emo[split].index,
+            description=f"Table selected for age and binary gender balance from all samples, limited to 20 samples per speaker.",
+        )
+        for field in ["speaker"]:
+            db[f"{age_tables_emotional_name}{split}"][field] = audformat.Column(scheme_id=field)
+            db[f"{age_tables_emotional_name}{split}"][field].set(splits_emo[split][field])
 
     db.save(build_dir)