diff --git a/config.json b/config.json
index 2a171ad1..c5434bf9 100644
--- a/config.json
+++ b/config.json
@@ -65,10 +65,6 @@
     "run_eval": true,
     "test_delay_epochs": 5,  //Until attention is aligned, testing only wastes computation time.
     "test_sentences_file": null,  // set a file to load sentences to be used for testing. If it is null then we use default english sentences.
-    "data_path": "/home/erogol/Data/LJSpeech-1.1/",  // DATASET-RELATED: can overwritten from command argument
-    "meta_file_train": "metadata_train.csv",      // DATASET-RELATED: metafile for training dataloader.
-    "meta_file_val": "metadata_val.csv",    // DATASET-RELATED: metafile for evaluation dataloader.
-    "dataset": "ljspeech",      // DATASET-RELATED: one of TTS.dataset.preprocessors depending on your target dataset. Use "tts_cache" for pre-computed dataset by extract_features.py
     "min_seq_len": 6,       // DATASET-RELATED: minimum text length to use in training
     "max_seq_len": 150,     // DATASET-RELATED: maximum text length
     "output_path": "../keep/",      // DATASET-RELATED: output path for all training outputs.
@@ -80,6 +76,17 @@
     "text_cleaner": "phoneme_cleaners",
     "use_speaker_embedding": false,     // use speaker embedding to enable multi-speaker learning.
     "style_wav_for_test": null,          // path to style wav file to be used in TacotronGST inference.
-    "use_gst": false        // TACOTRON ONLY: use global style tokens
+    "use_gst": false,       // TACOTRON ONLY: use global style tokens
+
+    "datasets":   // List of datasets. They all merged and they get different speaker_ids.
+        [
+            {
+                "name": "ljspeech",
+                "path": "/home/erogol/Data/LJSpeech-1.1/",
+                "meta_file_train": "metadata_train.csv",
+                "meta_file_val": "metadata_val.csv"
+            }
+        ]
+
 }
 
diff --git a/train.py b/train.py
index cbcfb1ec..b94f44fa 100644
--- a/train.py
+++ b/train.py
@@ -28,7 +28,7 @@ from TTS.utils.speakers import load_speaker_mapping, save_speaker_mapping, \
 from TTS.utils.synthesis import synthesis
 from TTS.utils.text.symbols import phonemes, symbols
 from TTS.utils.visual import plot_alignment, plot_spectrogram
-from TTS.datasets.preprocess import get_preprocessor_by_name
+from TTS.datasets.preprocess import load_meta_data
 from TTS.utils.radam import RAdam
 from TTS.utils.measures import alignment_diagonal_score
 
@@ -46,17 +46,7 @@ def setup_loader(ap, is_val=False, verbose=False):
     global meta_data_train
     global meta_data_eval
     if "meta_data_train" not in globals():
-        if c.meta_file_train is not None:
-            meta_data_train = get_preprocessor_by_name(
-                c.dataset)(c.data_path, c.meta_file_train)
-        else:
-            meta_data_train = get_preprocessor_by_name(c.dataset)(c.data_path)
-    if "meta_data_eval" not in globals() and c.run_eval:
-        if c.meta_file_val is not None:
-            meta_data_eval = get_preprocessor_by_name(
-                c.dataset)(c.data_path, c.meta_file_val)
-        else:
-            meta_data_eval, meta_data_train = split_dataset(meta_data_train)
+        meta_data_train, meta_data_eval = load_meta_data(c.datasets)
     if is_val and not c.run_eval:
         loader = None
     else: