Merge branch 'master' into dev/chinese_example

Author: dathudeptrai

tensorflow_tts/bin/preprocess.py

@@ -30,7 +30,10 @@
 from sklearn.preprocessing import StandardScaler
 from tqdm import tqdm
 
-from tensorflow_tts.processor import LJSpeechProcessor, BakerProcessor
+
+from tensorflow_tts.processor import LJSpeechProcessor
+from tensorflow_tts.processor import BakerProcessor
+
 from tensorflow_tts.utils import remove_outlier
 
 os.environ["CUDA_VISIBLE_DEVICES"] = ""
@@ -41,7 +44,6 @@ def parse_and_config():
     parser = argparse.ArgumentParser(
         description="Preprocess audio and text features "
         "(See detail in tensorflow_tts/bin/preprocess_dataset.py)."
-    )
     parser.add_argument(
         "--rootdir",
         default=None,
@@ -60,8 +62,8 @@ def parse_and_config():
         "--dataset",
         type=str,
         default="ljspeech",
-        choices=["ljspeech", "baker"],
-        help="Dataset to preprocess. Currently only LJSpeech.",
+        choices=["ljspeech, baker"],
+        help="Dataset to preprocess. Currently only (LJSpeech, baker)",
     )
     parser.add_argument(
         "--config", type=str, required=True, help="YAML format configuration file."
@@ -259,8 +261,7 @@ def preprocess():
 
     logging.info(f"Selected '{config['dataset']}' processor.")
     processor = dataset_processor[config["dataset"]](
-        config["rootdir"], cleaner_names="english_cleaners",
-        target_rate=config["sampling_rate"]
+        config["rootdir"], cleaner_names="english_cleaners"
     )
 
     # check output directories
@@ -289,13 +290,10 @@ def preprocess():
     # define map iterator
     def iterator_data(items_list):
         for item in items_list:
-            sample = processor.get_one_sample(item)
-            if sample is not None:
-                yield sample
+            yield processor.get_one_sample(item)
 
     train_iterator_data = iterator_data(train_split)
     valid_iterator_data = iterator_data(valid_split)
-
     p = Pool(config["n_cpus"])
 
     # preprocess train files and get statistics for normalizing
@@ -417,4 +415,5 @@ def compute_statistics():
     # save statistics to file
     logging.info("Saving computed statistics.")
     scaler_list = [(scaler_mel, ""), (scaler_energy, "_energy"), (scaler_f0, "_f0")]
-    save_statistics_to_file(scaler_list, config)
+    save_statistics_to_file(scaler_list, config)
+

tensorflow_tts/processor/ljspeech.py

@@ -122,7 +122,7 @@
 class LJSpeechProcessor(object):
     """LJSpeech processor."""
 
-    def __init__(self, data_dir, cleaner_names, target_rate=22050, metadata_filename="metadata.csv"):
+    def __init__(self, data_dir, cleaner_names, metadata_filename="metadata.csv"):
         self.data_dir = data_dir
         self.cleaner_names = cleaner_names