diff --git a/tensorflow_datasets/core/features/text/text_encoder.py b/tensorflow_datasets/core/features/text/text_encoder.py
index 6977d7014bb..6f853e96dd6 100644
--- a/tensorflow_datasets/core/features/text/text_encoder.py
+++ b/tensorflow_datasets/core/features/text/text_encoder.py
@@ -230,7 +230,9 @@ def __init__(self,
                oov_buckets=1,
                oov_token="UNK",
                lowercase=False,
-               tokenizer=None):
+               tokenizer=None,
+               strip_vocab=True,
+               decode_token_separator=" "):
     """Constructs a TokenTextEncoder.
 
     To load from a file saved with `TokenTextEncoder.save_to_file`, use
@@ -244,8 +246,14 @@ def __init__(self,
       lowercase: `bool`, whether to make all text and tokens lowercase.
       tokenizer: `Tokenizer`, responsible for converting incoming text into a
         list of tokens.
+      strip_vocab: `bool`, whether to strip whitespace from the beginning and
+        end of elements of `vocab_list`.
+      decode_token_separator: `str`, the string used to separate tokens when
+        decoding.
     """
-    self._vocab_list = [tf.compat.as_text(el).strip() for el in vocab_list]
+    self._vocab_list = [tf.compat.as_text(el) for el in vocab_list]
+    if strip_vocab:
+      self._vocab_list = [el.strip() for el in self._vocab_list]
     self._lowercase = lowercase
     if self._lowercase:
       self._vocab_list = [t.lower() for t in self._vocab_list]
@@ -261,6 +269,8 @@ def __init__(self,
     self._tokenizer = (tokenizer or Tokenizer(reserved_tokens=reserved_tokens))
     self._user_defined_tokenizer = tokenizer
 
+    self._decode_token_separator = decode_token_separator
+
   def encode(self, s):
     s = tf.compat.as_text(s)
     if self.lowercase:
@@ -286,7 +296,7 @@ def decode(self, ids):
         tokens.append(self._vocab_list[int_id])
       else:
         tokens.append(self._oov_token)
-    return " ".join(tokens)
+    return self._decode_token_separator.join(tokens)
 
   @property
   def vocab_size(self):