diff --git a/README.md b/README.md
index 0e05bee..aaab83d 100644
--- a/README.md
+++ b/README.md
@@ -42,6 +42,8 @@ python3 generate_samples.py 'okay, piper.' --max-samples 100 --batch-size 10 --o
 
 On an NVidia 2080 Ti with 11GB, a batch size of 100 was possible (generating approximately 100 samples per second).
 
+Setting `--max-speakers` to a value less than 904 (the number if LibriTTS) is recommended. Because very few samples of later speakers were in the original dataset, using them can cause audio artifacts.
+
 See `--help` for more options, including adjust the `--length-scales` (speaking speeds) and `--slerp-weights` (speaker blending) which are cycled per batch.
 
 ### Augmentation
diff --git a/generate_samples.py b/generate_samples.py
index 1b0d2f0..f1f098d 100755
--- a/generate_samples.py
+++ b/generate_samples.py
@@ -30,6 +30,11 @@ def main() -> None:
     parser.add_argument("--noise-scales", nargs="+", type=float, default=[0.667])
     parser.add_argument("--noise-scale-ws", nargs="+", type=float, default=[0.8])
     parser.add_argument("--output-dir", default="output")
+    parser.add_argument(
+        "--max-speakers",
+        type=int,
+        help="Maximum number of speakers to use (default: all)",
+    )
     args = parser.parse_args()
     logging.basicConfig(level=logging.DEBUG)
 
@@ -53,6 +58,8 @@ def main() -> None:
     voice = config["espeak"]["voice"]
     sample_rate = config["audio"]["sample_rate"]
     num_speakers = config["num_speakers"]
+    if args.max_speakers is not None:
+        num_speakers = min(num_speakers, args.max_speakers)
 
     phonemizer = Phonemizer(voice)
     phonemes_str = phonemizer.phonemize(args.text)
@@ -83,7 +90,7 @@ def main() -> None:
         )
     )
 
-    speakers_iter = it.product(range(num_speakers), range(num_speakers))
+    speakers_iter = it.cycle(it.product(range(num_speakers), range(num_speakers)))
     speakers_batch = list(it.islice(speakers_iter, 0, args.batch_size))
     batch_idx = 0
     while speakers_batch: