diff --git a/torchaudio/datasets/yesno.py b/torchaudio/datasets/yesno.py
index 6d0d2c0a5f..614cd4c7a5 100644
--- a/torchaudio/datasets/yesno.py
+++ b/torchaudio/datasets/yesno.py
@@ -1,14 +1,16 @@
 import os
 from pathlib import Path
+from dataclasses import dataclass
 from typing import List, Tuple, Union
 
 from torch import Tensor
-from torch.utils.data import Dataset
+from torch.utils.data import Dataset, IterDataPipe
 
 import torchaudio
 from torchaudio.datasets.utils import (
     download_url,
     extract_archive,
+
 )
 
 
@@ -17,10 +19,108 @@
         "folder_in_archive": "waves_yesno",
         "url": "http://www.openslr.org/resources/1/waves_yesno.tar.gz",
         "checksum": "30301975fd8c5cac4040c261c0852f57cfa8adbbad2ce78e77e4986957445f27",
+        "files": [
+            "0_0_0_0_1_1_1_1.wav",
+            "0_0_0_1_0_0_0_1.wav",
+            "0_0_0_1_0_1_1_0.wav",
+            "0_0_1_0_0_0_1_0.wav",
+            "0_0_1_0_0_1_1_0.wav",
+            "0_0_1_0_0_1_1_1.wav",
+            "0_0_1_0_1_0_0_0.wav",
+            "0_0_1_0_1_0_0_1.wav",
+            "0_0_1_0_1_0_1_1.wav",
+            "0_0_1_1_0_0_0_1.wav",
+            "0_0_1_1_0_1_0_0.wav",
+            "0_0_1_1_0_1_1_0.wav",
+            "0_0_1_1_0_1_1_1.wav",
+            "0_0_1_1_1_0_0_0.wav",
+            "0_0_1_1_1_0_0_1.wav",
+            "0_0_1_1_1_1_0_0.wav",
+            "0_0_1_1_1_1_1_0.wav",
+            "0_1_0_0_0_1_0_0.wav",
+            "0_1_0_0_0_1_1_0.wav",
+            "0_1_0_0_1_0_1_0.wav",
+            "0_1_0_0_1_0_1_1.wav",
+            "0_1_0_1_0_0_0_0.wav",
+            "0_1_0_1_1_0_1_0.wav",
+            "0_1_0_1_1_1_0_0.wav",
+            "0_1_1_0_0_1_1_0.wav",
+            "0_1_1_0_0_1_1_1.wav",
+            "0_1_1_1_0_0_0_0.wav",
+            "0_1_1_1_0_0_1_0.wav",
+            "0_1_1_1_0_1_0_1.wav",
+            "0_1_1_1_1_0_1_0.wav",
+            "0_1_1_1_1_1_1_1.wav",
+            "1_0_0_0_0_0_0_0.wav",
+            "1_0_0_0_0_0_0_1.wav",
+            "1_0_0_0_0_0_1_1.wav",
+            "1_0_0_0_1_0_0_1.wav",
+            "1_0_0_1_0_1_1_1.wav",
+            "1_0_1_0_1_0_0_1.wav",
+            "1_0_1_1_0_1_1_1.wav",
+            "1_0_1_1_1_0_1_0.wav",
+            "1_0_1_1_1_1_0_1.wav",
+            "1_1_0_0_0_0_0_1.wav",
+            "1_1_0_0_0_1_1_1.wav",
+            "1_1_0_0_1_0_1_0.wav",
+            "1_1_0_0_1_0_1_1.wav",
+            "1_1_0_0_1_1_1_0.wav",
+            "1_1_0_1_0_1_0_0.wav",
+            "1_1_0_1_0_1_1_0.wav",
+            "1_1_0_1_1_0_0_1.wav",
+            "1_1_0_1_1_0_1_1.wav",
+            "1_1_0_1_1_1_1_0.wav",
+            "1_1_1_0_0_0_0_1.wav",
+            "1_1_1_0_0_1_0_1.wav",
+            "1_1_1_0_0_1_1_1.wav",
+            "1_1_1_0_1_0_1_0.wav",
+            "1_1_1_0_1_0_1_1.wav",
+            "1_1_1_1_0_0_1_0.wav",
+            "1_1_1_1_0_1_0_0.wav",
+            "1_1_1_1_1_0_0_0.wav",
+            "1_1_1_1_1_1_0_0.wav",
+            "1_1_1_1_1_1_1_1.wav",
+        ]
     }
 }
 
 
+@dataclass
+class YesNoItem:
+    path: str
+    label: List[int]
+    waveform: Tensor
+    sample_rate: int
+
+
+class ListYesNoItems(IterDataPipe):
+    """Given a root directory, return the list of files"""
+    def __init__(self, root):
+        self.data_dir = os.path.join(root, 'waves_yesno')
+        self.files = _RELEASE_CONFIGS['release1']['files']
+
+    def __iter__(self):
+        for filename in self.files:
+            path = os.path.join(self.data_dir, filename)
+            label = [int(c) for c in path.split("_")]
+            yield path, label
+
+
+class LoadYesNoItem(IterDataPipe):
+    def __init__(self, data_pipe):
+        self.data_pipe = data_pipe
+
+    def __iter__(self):
+        for path, label in self.data_pipe:
+            waveform, sample_rate = torchaudio.load(path)
+            yield YesNoItem(path, label, waveform, sample_rate)
+
+
+def get_yesno_dataset(root_dir: str):  # , download=False, url=_RELEASE_CONFIGS["release1"]["url"]):
+    # TODO: download dataset if necessary
+    return LoadYesNoItem(ListYesNoItems(root_dir))
+
+
 class YESNO(Dataset):
     """Create a Dataset for YesNo.