diff --git a/lhotse/recipes/commonvoice.py b/lhotse/recipes/commonvoice.py
index fd84329da..46a08cd91 100644
--- a/lhotse/recipes/commonvoice.py
+++ b/lhotse/recipes/commonvoice.py
@@ -9,6 +9,7 @@
 How does it work?
 We are crowdsourcing an open-source dataset of voices. Donate your voice, validate the accuracy of other people's clips, make the dataset better for everyone.
 """
+import csv
 import logging
 import math
 import numbers
@@ -149,14 +150,13 @@ def _parse_utterance(
     language: str,
     audio_info: str,
 ) -> Optional[Tuple[Recording, SupervisionSegment]]:
-    audio_info = audio_info.split("\t", -1)
-    audio_path = lang_path / "clips" / audio_info[1]
+    audio_path = lang_path / "clips" / audio_info["path"]
 
     if not audio_path.is_file():
         logging.info(f"No such file: {audio_path}")
         return None
 
-    recording_id = Path(audio_info[1]).stem
+    recording_id = Path(audio_info["path"]).stem
     recording = Recording.from_file(path=audio_path, recording_id=recording_id)
 
     segment = SupervisionSegment(
@@ -166,12 +166,13 @@ def _parse_utterance(
         duration=recording.duration,
         channel=0,
         language=language,
-        speaker=audio_info[0],
-        text=audio_info[2].strip(),
-        gender=audio_info[6],
+        speaker=audio_info["client_id"],
+        text=audio_info["sentence"].strip(),
+        gender=audio_info["gender"],
         custom={
-            "age": audio_info[5],
-            "accents": audio_info[7],
+            "age": audio_info["age"],
+            "accents": audio_info["accents"],
+            "variant": audio_info["variant"],
         },
     )
     return recording, segment
@@ -207,19 +208,22 @@ def _prepare_part(
             futures = []
             recordings = []
             supervisions = []
+            audio_infos = []
 
-            with open(tsv_path) as f:
-                audio_infos = iter(f.readlines())
+            with open(tsv_path, "r") as f:
 
-            for audio_info in tqdm(audio_infos, desc="Distributing tasks"):
-                futures.append(
-                    ex.submit(
-                        _parse_utterance,
-                        lang_path,
-                        lang,
-                        audio_info,
+                # Note: using QUOTE_NONE as CV dataset contains unbalanced quotes, cleanup needed later
+                audio_infos = csv.DictReader(f, delimiter="\t", quoting=csv.QUOTE_NONE)
+
+                for audio_info in tqdm(audio_infos, desc="Distributing tasks"):
+                    futures.append(
+                        ex.submit(
+                            _parse_utterance,
+                            lang_path,
+                            lang,
+                            audio_info,
+                        )
                     )
-                )
 
             for future in tqdm(futures, desc="Processing"):
                 result = future.result()