Dataset Preview
Go to dataset viewer
The dataset preview is not available for this split.
Cannot load the dataset split (in streaming mode) to extract the first rows.
Error code:   StreamingRowsError
Exception:    ValueError
Message:      Cannot seek streaming HTTP file
Traceback:    Traceback (most recent call last):
                File "/src/workers/datasets_based/src/datasets_based/workers/", line 485, in compute_first_rows_response
                  rows = get_rows(
                File "/src/workers/datasets_based/src/datasets_based/workers/", line 120, in decorator
                  return func(*args, **kwargs)
                File "/src/workers/datasets_based/src/datasets_based/workers/", line 176, in get_rows
                  rows_plus_one = list(itertools.islice(ds, rows_max_number + 1))
                File "/src/workers/datasets_based/.venv/lib/python3.9/site-packages/datasets/", line 846, in __iter__
                  for key, example in self._iter():
                File "/src/workers/datasets_based/.venv/lib/python3.9/site-packages/datasets/", line 788, in _iter
                  yield from ex_iterable
                File "/src/workers/datasets_based/.venv/lib/python3.9/site-packages/datasets/", line 113, in __iter__
                  yield from self.generate_examples_fn(**self.kwargs)
                File "/tmp/modules-cache/datasets_modules/datasets/cmu_hinglish_dog/b9e670cb8154a26ca6e5668630f68a36423e6ccf62c880fb828f232e7834e834/", line 135, in _generate_examples
                  english_files_train = os.listdir(os.path.join(data_dir_en, "train"))
                File "/src/workers/datasets_based/.venv/lib/python3.9/site-packages/datasets/", line 69, in wrapper
                  return function(*args, use_auth_token=use_auth_token, **kwargs)
                File "/src/workers/datasets_based/.venv/lib/python3.9/site-packages/datasets/download/", line 496, in xlistdir
                  fs, *_ = fsspec.get_fs_token_paths(path, storage_options=storage_options)
                File "/src/workers/datasets_based/.venv/lib/python3.9/site-packages/fsspec/", line 606, in get_fs_token_paths
                  fs = filesystem(protocol, **inkwargs)
                File "/src/workers/datasets_based/.venv/lib/python3.9/site-packages/fsspec/", line 284, in filesystem
                  return cls(**storage_options)
                File "/src/workers/datasets_based/.venv/lib/python3.9/site-packages/fsspec/", line 76, in __call__
                  obj = super().__call__(*args, **kwargs)
                File "/src/workers/datasets_based/.venv/lib/python3.9/site-packages/fsspec/implementations/", line 54, in __init__
         = zipfile.ZipFile(, mode=mode)
                File "/usr/local/lib/python3.9/", line 1266, in __init__
                File "/usr/local/lib/python3.9/", line 1329, in _RealGetContents
                  endrec = _EndRecData(fp)
                File "/usr/local/lib/python3.9/", line 263, in _EndRecData
        , 2)
                File "/src/workers/datasets_based/.venv/lib/python3.9/site-packages/fsspec/implementations/", line 702, in seek
                  raise ValueError("Cannot seek streaming HTTP file")
              ValueError: Cannot seek streaming HTTP file

Need help to make the dataset viewer work? Open an discussion for direct support.

Dataset Card for CMU Document Grounded Conversations

Dataset Summary

This is a collection of text conversations in Hinglish (code mixing between Hindi-English) and their corresponding English versions. Can be used for Translating between the two. The dataset has been provided by Prof. Alan Black's group from CMU.

Supported Tasks and Leaderboards

  • abstractive-mt


Dataset Structure

Data Instances

A typical data point comprises a Hinglish text, with key hi_en and its English version with key en. The docIdx contains the current section index of the wiki document when the utterance is said. There are in total 4 sections for each document. The uid has the user id of this utterance.

An example from the CMU_Hinglish_DoG train set looks as follows:

{'rating': 2,
 'wikiDocumentIdx': 13,
 'utcTimestamp': '2018-03-16T17:48:22.037Z',
 'uid': 'user2',
 'date': '2018-03-16T17:47:21.964Z',
 'uid2response': {'response': [1, 2, 3, 5], 'type': 'finish'},
 'uid1LogInTime': '2018-03-16T17:47:21.964Z',
 'user2_id': 'USR664',
 'uid1LogOutTime': '2018-03-16T18:02:29.072Z',
 'whoSawDoc': ['user1', 'user2'],
 'status': 1,
 'docIdx': 0,
 'uid1response': {'response': [1, 2, 3, 4], 'type': 'finish'},
 'translation': {'en': 'The director is Zack Snyder, 27% Rotten Tomatoes, 4.9/10.',
  'hi_en': 'Zack Snyder director hai, 27% Rotten Tomatoes, 4.9/10.'}}

Data Fields

  • date: the time the file is created, as a string
  • docIdx: the current section index of the wiki document when the utterance is said. There are in total 4 sections for each document.
  • translation:
    • hi_en: The text in Hinglish
    • en: The text in English
  • uid: the user id of this utterance.
  • utcTimestamp: the server utc timestamp of this utterance, as a string
  • rating: A number from 1 or 2 or 3. A larger number means the quality of the conversation is better.
  • status: status as an integer
  • uid1LogInTime: optional login time of user 1, as a string
  • uid1LogOutTime: optional logout time of user 1, as a string
  • uid1response: a json object contains the status and response of user after finishing the conversation. Fields in the object includes:
    • type: should be one of ['finish', 'abandon','abandonWithouAnsweringFeedbackQuestion']. 'finish' means the user successfully finishes the conversation, either by completing 12 or 15 turns or in the way that the other user leaves the conversation first. 'abandon' means the user abandons the conversation in the middle, but entering the feedback page. 'abandonWithouAnsweringFeedbackQuestion' means the user just disconnects or closes the web page without providing the feedback.
    • response: the answer to the post-conversation questions. The worker can choose multiple of them. The options presented to the user are as follows: For type 'finish' 1: The conversation is understandable. 2: The other user is actively responding me. 3: The conversation goes smoothly. For type 'abandon' 1: The other user is too rude. 2: I don't know how to proceed with the conversation. 3: The other user is not responding to me. For users given the document 4: I have watched the movie before. 5: I have not watched the movie before. For the users without the document 4: I will watch the movie after the other user's introduction. 5: I will not watch the movie after the other user's introduction.
  • uid2response: same as uid1response
  • user2_id: the generated user id of user 2
  • whoSawDoc: Should be one of ['user1'], ['user2'], ['user1', 'user2']. Indicating which user read the document.
  • wikiDocumentId: the index of the wiki document.

Data Splits

name train validation test
CMU DOG 8060 942 960

Dataset Creation

[More Information Needed]

Curation Rationale

[More Information Needed]

Source Data

The Hinglish dataset is derived from the original CMU DoG (Document Grounded Conversations Dataset). More info about that can be found in the repo

Initial Data Collection and Normalization

[More Information Needed]

Who are the source language producers?

[More Information Needed]


[More Information Needed]

Annotation process

[More Information Needed]

Who are the annotators?

[More Information Needed]

Personal and Sensitive Information

[More Information Needed]

Considerations for Using the Data

Social Impact of Dataset

The purpose of this dataset is to help develop better question answering systems.

Discussion of Biases

[More Information Needed]

Other Known Limitations

[More Information Needed]

Additional Information

Dataset Curators

The dataset was initially created by Prof Alan W Black's group at CMU

Licensing Information

[More Information Needed]

Citation Information

    title={A Dataset for Document Grounded Conversations},
    author={Zhou, Kangyan and Prabhumoye, Shrimai and Black, Alan W},
    booktitle={Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing}


Thanks to @Ishan-Kumar2 for adding this dataset.

Downloads last month

Models trained or fine-tuned on cmu_hinglish_dog