Text cleaning

.run/{prep_data.run.xml → prep_push_to_hf.run.xml}

@@ -1,5 +1,5 @@
 <component name="ProjectRunConfigurationManager">
-  <configuration default="false" name="prep_push_to_hf" type="PythonConfigurationType" factoryName="Python" nameIsGenerated="true">
+  <configuration default="false" name="prep_push_to_hf" type="PythonConfigurationType" factoryName="Python">
     <module name="Kendex" />
     <option name="INTERPRETER_OPTIONS" value="" />
     <option name="PARENT_ENVS" value="true" />
@@ -7,7 +7,7 @@
       <env name="PYTHONUNBUFFERED" value="1" />
     </envs>
     <option name="SDK_HOME" value="" />
-    <option name="WORKING_DIRECTORY" value="$PROJECT_DIR$/scripts" />
+    <option name="WORKING_DIRECTORY" value="$PROJECT_DIR$/kendex" />
     <option name="IS_MODULE_SDK" value="true" />
     <option name="ADD_CONTENT_ROOTS" value="true" />
     <option name="ADD_SOURCE_ROOTS" value="true" />
@@ -31,7 +31,7 @@
       <option name="region" />
       <option name="useCurrentConnection" value="false" />
     </EXTENSION>
-    <option name="SCRIPT_NAME" value="$PROJECT_DIR$/leviticus/prep_push_to_hf.py" />
+    <option name="SCRIPT_NAME" value="$PROJECT_DIR$/kendex/prep_push_to_hf.py" />
     <option name="PARAMETERS" value="" />
     <option name="SHOW_COMMAND_LINE" value="false" />
     <option name="EMULATE_TERMINAL" value="false" />

kendex/prep_push_to_hf.py

@@ -22,6 +22,12 @@ def text_filter(item):
     return MIN_LEN < len([i for i in item.split(" ") if len(i) > 0]) < MAX_LEN
 
 
+def text_mapper(item):
+    text = item["text"]
+    item["normalized_text"] = normalize(text)
+    return item
+
+
 def create_dataset(item):
     dataset = Dataset.from_pandas(item)
     dataset = dataset.cast_column("audio", Audio(sampling_rate=16_000))
@@ -42,7 +48,6 @@ def main():
         "audio": wavs,
         "file": [basename(w) for w in wavs],
         "text": metadata[1],
-        "norm": metadata[1].map(lambda x: normalize(x)),
         "duration": [librosa.get_duration(path=w) for w in wavs],
     }
 
@@ -51,7 +56,9 @@ def main():
     train, test = np.split(df, [int(0.9 * len(df))])
 
     train_dataset = create_dataset(train)
+    train_dataset = train_dataset.map(text_mapper)
     test_dataset = create_dataset(test)
+    test_dataset = test_dataset.map(text_mapper)
 
     full_dataset = DatasetDict({"train": train_dataset, "test": test_dataset})
     full_dataset.push_to_hub("michaelnetbiz/Kendex")