diff --git a/lhotse/cut/set.py b/lhotse/cut/set.py
index a878ada21..86b7f46cd 100644
--- a/lhotse/cut/set.py
+++ b/lhotse/cut/set.py
@@ -2632,6 +2632,53 @@ def to_huggingface_dataset(self):
 
         return export_cuts_to_hf(self)
 
+    @staticmethod
+    def from_huggingface_dataset(
+        *dataset_args,
+        audio_key: str = "audio",
+        text_key: str = "sentence",
+        lang_key: str = "language",
+        gender_key: str = "gender",
+        **dataset_kwargs,
+    ):
+        """
+        Initializes a Lhotse CutSet from an existing HF dataset,
+        or args/kwargs passed on to ``datasets.load_dataset()``.
+
+        Use ``audio_key``, ``text_key``, ``lang_key`` and ``gender_key`` options to indicate which keys in dict examples
+        returned from HF Dataset should be looked up for audio, transcript, language, and gender respectively.
+        The remaining keys in HF dataset examples will be stored inside ``cut.custom`` dictionary.
+
+        Example with existing HF dataset::
+
+            >>> import datasets
+            ... dataset = datasets.load_dataset("mozilla-foundation/common_voice_11_0", "hi", split="test")
+            ... dataset = dataset.map(some_transform)
+            ... cuts = CutSet.from_huggingface_dataset(dataset)
+            ... for cut in cuts:
+            ...     pass
+
+        Example providing HF dataset init args/kwargs::
+
+            >>> import datasets
+            ... cuts = CutSet.from_huggingface_dataset("mozilla-foundation/common_voice_11_0", "hi", split="test")
+            ... for cut in cuts:
+            ...     pass
+
+        """
+        from lhotse.hf import LazyHFDatasetIterator
+
+        return CutSet(
+            LazyHFDatasetIterator(
+                *dataset_args,
+                audio_key=audio_key,
+                text_key=text_key,
+                lang_key=lang_key,
+                gender_key=gender_key,
+                **dataset_kwargs,
+            )
+        )
+
     def __repr__(self) -> str:
         try:
             len_val = len(self)
diff --git a/lhotse/hf.py b/lhotse/hf.py
index 493087ad9..1cfdb4bad 100644
--- a/lhotse/hf.py
+++ b/lhotse/hf.py
@@ -1,12 +1,14 @@
 """
-╔══════════════════════════════════════╗
-║ Export CutSet to HuggingFace Dataset ║
-╚══════════════════════════════════════╝
+╔═════════════════════════════════════════════╗
+║ Export/Import CutSet to HuggingFace Dataset ║
+╚═════════════════════════════════════════════╝
 """
+from hashlib import md5
 from typing import Any, Dict, List, Optional, Set, Tuple, Union
 
+from lhotse import Recording, SupervisionSegment
 from lhotse.cut import CutSet, MonoCut
-from lhotse.utils import is_module_available
+from lhotse.utils import Pathlike, is_module_available
 
 
 def contains_only_mono_cuts(cutset: CutSet) -> bool:
@@ -301,3 +303,78 @@ def export_cuts_to_hf(cutset: CutSet):
         )
 
     return Dataset.from_dict(dataset_dict, features=dataset_info)
+
+
+class LazyHFDatasetIterator:
+    """
+    Thin wrapper on top of HF datasets objects that allows to interact with them through a Lhotse CutSet.
+    It can be initialized with an existing HF dataset, or args/kwargs passed on to ``datasets.load_dataset()``.
+
+    Use ``audio_key``, ``text_key``, ``lang_key`` and ``gender_key`` options to indicate which keys in dict examples
+    returned from HF Dataset should be looked up for audio, transcript, language, and gender respectively.
+    The remaining keys in HF dataset examples will be stored inside ``cut.custom`` dictionary.
+
+    Example with existing HF dataset::
+
+        >>> import datasets
+        ... dataset = datasets.load_dataset("mozilla-foundation/common_voice_11_0", "hi", split="test")
+        ... dataset = dataset.map(some_transform)
+        ... cuts_it = LazyHFDatasetIterator(dataset)
+        ... for cut in cuts_it:
+        ...     pass
+
+    Example providing HF dataset init args/kwargs::
+
+        >>> import datasets
+        ... cuts_it = LazyHFDatasetIterator("mozilla-foundation/common_voice_11_0", "hi", split="test")
+        ... for cut in cuts_it:
+        ...     pass
+
+    """
+
+    def __init__(
+        self,
+        *dataset_args,
+        audio_key: str = "audio",
+        text_key: str = "sentence",
+        lang_key: str = "language",
+        gender_key: str = "gender",
+        **dataset_kwargs
+    ):
+        assert is_module_available("datasets")
+        self.audio_key = audio_key
+        self.text_key = text_key
+        self.lang_key = lang_key
+        self.gender_key = gender_key
+        self.dataset_args = dataset_args
+        self.dataset_kwargs = dataset_kwargs
+
+    def __iter__(self):
+        from datasets import Audio, Dataset, IterableDataset, load_dataset
+
+        if len(self.dataset_args) == 1 and isinstance(
+            self.dataset_args[0], (Dataset, IterableDataset)
+        ):
+            dataset = self.dataset_args[0]
+        else:
+            dataset = load_dataset(*self.dataset_args, **self.dataset_kwargs)
+
+        dataset = dataset.cast_column(self.audio_key, Audio(decode=False))
+        for item in dataset:
+            audio_data = item.pop(self.audio_key)
+            recording = Recording.from_bytes(
+                audio_data["bytes"], recording_id=md5(audio_data["bytes"]).hexdigest()
+            )
+            supervision = SupervisionSegment(
+                id=recording.id,
+                recording_id=recording.id,
+                start=0.0,
+                duration=recording.duration,
+                text=item.pop(self.text_key, None),
+                language=item.pop(self.lang_key, None),
+                gender=item.pop(self.gender_key, None),
+            )
+            cut = recording.to_cut()
+            cut.supervisions = [supervision]
+            cut.custom = item
+            yield cut