diff --git a/egs/librispeech/ASR/pruned_transducer_stateless/train.py b/egs/librispeech/ASR/pruned_transducer_stateless/train.py
index f0ea12d62..c360d025a 100755
--- a/egs/librispeech/ASR/pruned_transducer_stateless/train.py
+++ b/egs/librispeech/ASR/pruned_transducer_stateless/train.py
@@ -811,13 +811,23 @@ def run(rank, world_size, args):
 
     train_cuts = train_cuts.filter(remove_short_and_long_utt)
 
-    num_left = len(train_cuts)
-    num_removed = num_in_total - num_left
-    removed_percent = num_removed / num_in_total * 100
+    try:
+        num_left = len(train_cuts)
+        num_removed = num_in_total - num_left
+        removed_percent = num_removed / num_in_total * 100
 
-    logging.info(f"Before removing short and long utterances: {num_in_total}")
-    logging.info(f"After removing short and long utterances: {num_left}")
-    logging.info(f"Removed {num_removed} utterances ({removed_percent:.5f}%)")
+        logging.info(
+            f"Before removing short and long utterances: {num_in_total}"
+        )
+        logging.info(f"After removing short and long utterances: {num_left}")
+        logging.info(
+            f"Removed {num_removed} utterances ({removed_percent:.5f}%)"
+        )
+    except TypeError as e:
+        # You can ignore this error as previous versions of Lhotse work fine
+        # for the above code. In recent versions of Lhotse, it uses
+        # lazy filter, producing cutsets that don't have the __len__  method
+        logging.info(str(e))
 
     if params.start_batch > 0 and checkpoints and "sampler" in checkpoints:
         # We only load the sampler's state dict when it loads a checkpoint
diff --git a/egs/librispeech/ASR/transducer_stateless/train.py b/egs/librispeech/ASR/transducer_stateless/train.py
index d6827c17c..89f754b20 100755
--- a/egs/librispeech/ASR/transducer_stateless/train.py
+++ b/egs/librispeech/ASR/transducer_stateless/train.py
@@ -653,13 +653,23 @@ def run(rank, world_size, args):
 
     train_cuts = train_cuts.filter(remove_short_and_long_utt)
 
-    num_left = len(train_cuts)
-    num_removed = num_in_total - num_left
-    removed_percent = num_removed / num_in_total * 100
+    try:
+        num_left = len(train_cuts)
+        num_removed = num_in_total - num_left
+        removed_percent = num_removed / num_in_total * 100
 
-    logging.info(f"Before removing short and long utterances: {num_in_total}")
-    logging.info(f"After removing short and long utterances: {num_left}")
-    logging.info(f"Removed {num_removed} utterances ({removed_percent:.5f}%)")
+        logging.info(
+            f"Before removing short and long utterances: {num_in_total}"
+        )
+        logging.info(f"After removing short and long utterances: {num_left}")
+        logging.info(
+            f"Removed {num_removed} utterances ({removed_percent:.5f}%)"
+        )
+    except TypeError as e:
+        # You can ignore this error as previous versions of Lhotse work fine
+        # for the above code. In recent versions of Lhotse, it uses
+        # lazy filter, producing cutsets that don't have the __len__  method
+        logging.info(str(e))
 
     train_dl = librispeech.train_dataloaders(train_cuts)
 
diff --git a/egs/librispeech/ASR/transducer_stateless2/train.py b/egs/librispeech/ASR/transducer_stateless2/train.py
index 2111795ea..8ceffb489 100755
--- a/egs/librispeech/ASR/transducer_stateless2/train.py
+++ b/egs/librispeech/ASR/transducer_stateless2/train.py
@@ -641,13 +641,23 @@ def run(rank, world_size, args):
 
     train_cuts = train_cuts.filter(remove_short_and_long_utt)
 
-    num_left = len(train_cuts)
-    num_removed = num_in_total - num_left
-    removed_percent = num_removed / num_in_total * 100
+    try:
+        num_left = len(train_cuts)
+        num_removed = num_in_total - num_left
+        removed_percent = num_removed / num_in_total * 100
 
-    logging.info(f"Before removing short and long utterances: {num_in_total}")
-    logging.info(f"After removing short and long utterances: {num_left}")
-    logging.info(f"Removed {num_removed} utterances ({removed_percent:.5f}%)")
+        logging.info(
+            f"Before removing short and long utterances: {num_in_total}"
+        )
+        logging.info(f"After removing short and long utterances: {num_left}")
+        logging.info(
+            f"Removed {num_removed} utterances ({removed_percent:.5f}%)"
+        )
+    except TypeError as e:
+        # You can ignore this error as previous versions of Lhotse work fine
+        # for the above code. In recent versions of Lhotse, it uses
+        # lazy filter, producing cutsets that don't have the __len__  method
+        logging.info(str(e))
 
     train_dl = librispeech.train_dataloaders(train_cuts)