diff --git a/src/python/larynx_train/preprocess.py b/src/python/larynx_train/preprocess.py
index 9fe6a7b..9257367 100644
--- a/src/python/larynx_train/preprocess.py
+++ b/src/python/larynx_train/preprocess.py
@@ -42,6 +42,9 @@ def main() -> None:
     )
     parser.add_argument("--cache-dir", help="Directory to cache processed audio files")
     parser.add_argument("--max-workers", type=int)
+    parser.add_argument(
+        "--single-speaker", action="store_true", help="Force single speaker dataset"
+    )
     parser.add_argument(
         "--debug", action="store_true", help="Print DEBUG messages to the console"
     )
@@ -75,7 +78,7 @@ def main() -> None:
     _LOGGER.debug("Counting number of speakers/utterances in the dataset")
     speaker_counts: Counter[str] = Counter()
     num_utterances = 0
-    for utt in make_dataset(args.input_dir):
+    for utt in make_dataset(args.input_dir, args.single_speaker):
         speaker = utt.speaker or ""
         speaker_counts[speaker] += 1
         num_utterances += 1
@@ -142,7 +145,9 @@ def main() -> None:
         "Processing %s utterance(s) with %s worker(s)", num_utterances, args.max_workers
     )
     with open(args.output_dir / "dataset.jsonl", "w", encoding="utf-8") as dataset_file:
-        for utt_batch in batched(make_dataset(args.input_dir), batch_size):
+        for utt_batch in batched(
+            make_dataset(args.input_dir, args.single_speaker), batch_size
+        ):
             queue_in.put(utt_batch)
 
         _LOGGER.debug("Waiting for jobs to finish")
@@ -226,7 +231,7 @@ class PathEncoder(json.JSONEncoder):
         return super().default(o)
 
 
-def ljspeech_dataset(dataset_dir: Path) -> Iterable[Utterance]:
+def ljspeech_dataset(dataset_dir: Path, is_single_speaker: bool) -> Iterable[Utterance]:
     # filename|speaker|text
     # speaker is optional
     metadata_path = dataset_dir / "metadata.csv"
@@ -242,7 +247,7 @@ def ljspeech_dataset(dataset_dir: Path) -> Iterable[Utterance]:
             assert len(row) >= 2, "Not enough colums"
 
             speaker: Optional[str] = None
-            if len(row) == 2:
+            if is_single_speaker or (len(row) == 2):
                 filename, text = row[0], row[-1]
             else:
                 filename, speaker, text = row[0], row[1], row[-1]
@@ -269,7 +274,7 @@ def ljspeech_dataset(dataset_dir: Path) -> Iterable[Utterance]:
             yield Utterance(text=text, audio_path=wav_path, speaker=speaker)
 
 
-def mycroft_dataset(dataset_dir: Path) -> Iterable[Utterance]:
+def mycroft_dataset(dataset_dir: Path, is_single_speaker: bool) -> Iterable[Utterance]:
     for info_path in dataset_dir.glob("*.info"):
         wav_path = info_path.with_suffix(".wav")
         if wav_path.exists():