diff --git a/pipe/pipe.py b/pipe/pipe.py
index b65837e..6589a40 100644
--- a/pipe/pipe.py
+++ b/pipe/pipe.py
@@ -30,6 +30,28 @@ def __init__(self, spark: SparkSession, filetype: str = "hdf5"):
         else:
             raise ValueError
 
+    def metadata_pipe(self, metapath: Path, labels:list,
+                      namepattern: str="metadata{}.json") -> dict:
+        """
+        Loads metadata for each target label from a set of json files and
+        return them as a hierarchical dictionary.
+
+        Args:
+            metapath (Path): Path to the metadata files.
+            labels (list): List of target labels.
+            namepattern (str): Name pattern for the metadata files.
+
+        Returns:
+            metadata: Hierarchical dictionary of metadata.
+        """
+
+        metadata = {}
+        for label in labels:
+            with open(metapath/namepattern.format(label), 'r') as f:
+                metadata[label] = json.load(f)
+
+        return metadata
+
     def spectrogram_pipe_hdf5(self, specpath: Path, labels: list,
                               namepattern:str="averaged_spectrogram{}.hdf5"
             ) -> np.ndarray:
@@ -43,13 +65,14 @@ def spectrogram_pipe_hdf5(self, specpath: Path, labels: list,
         Returns:
         """
         
+        metadata = self.metadata_pipe(specpath, labels)
         spectrograms = []
         for label in labels:
             filename = namepattern.format(label)
+            meta = metadata[label]
             with h5py.File(specpath/filename, 'r') as f:
-                spectrograms.append(
-                        Row(label=label,
-                            spectrogram=f['spectrogram'][:].tolist()))
+                meta["spectrogram"] = f['spectrogram'][:].tolist()
+            spectrograms.append(Row(**meta))
 
         return self.spark.createDataFrame(spectrograms)