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.gitattributes

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README.md

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----
-annotations_creators:
-- expert-generated
-- found
-- no-annotation
-language_creators:
-- found
-language:
-- chr
-- en
-license:
-- other
-multilinguality:
-- monolingual
-- multilingual
-- translation
-size_categories:
-- 100K<n<1M
-- 10K<n<100K
-- 1K<n<10K
-source_datasets:
-- original
-task_categories:
-- fill-mask
-- text-generation
-- translation
-task_ids:
-- language-modeling
-- masked-language-modeling
-paperswithcode_id: chren
-configs:
-- monolingual
-- monolingual_raw
-- parallel
-- parallel_raw
-dataset_info:
-- config_name: monolingual_raw
-  features:
-  - name: text_sentence
-    dtype: string
-  - name: text_title
-    dtype: string
-  - name: speaker
-    dtype: string
-  - name: date
-    dtype: int32
-  - name: type
-    dtype: string
-  - name: dialect
-    dtype: string
-  splits:
-  - name: full
-    num_bytes: 1210828
-    num_examples: 5210
-  download_size: 28899321
-  dataset_size: 1210828
-- config_name: parallel_raw
-  features:
-  - name: line_number
-    dtype: string
-  - name: sentence_pair
-    dtype:
-      translation:
-        languages:
-        - en
-        - chr
-  - name: text_title
-    dtype: string
-  - name: speaker
-    dtype: string
-  - name: date
-    dtype: int32
-  - name: type
-    dtype: string
-  - name: dialect
-    dtype: string
-  splits:
-  - name: full
-    num_bytes: 5012923
-    num_examples: 14151
-  download_size: 28899321
-  dataset_size: 5012923
-- config_name: monolingual
-  features:
-  - name: sentence
-    dtype: string
-  splits:
-  - name: chr
-    num_bytes: 882848
-    num_examples: 5210
-  - name: en5000
-    num_bytes: 615295
-    num_examples: 5000
-  - name: en10000
-    num_bytes: 1211645
-    num_examples: 10000
-  - name: en20000
-    num_bytes: 2432378
-    num_examples: 20000
-  - name: en50000
-    num_bytes: 6065780
-    num_examples: 49999
-  - name: en100000
-    num_bytes: 12130564
-    num_examples: 100000
-  download_size: 28899321
-  dataset_size: 23338510
-- config_name: parallel
-  features:
-  - name: sentence_pair
-    dtype:
-      translation:
-        languages:
-        - en
-        - chr
-  splits:
-  - name: train
-    num_bytes: 3089658
-    num_examples: 11639
-  - name: dev
-    num_bytes: 260409
-    num_examples: 1000
-  - name: out_dev
-    num_bytes: 78134
-    num_examples: 256
-  - name: test
-    num_bytes: 264603
-    num_examples: 1000
-  - name: out_test
-    num_bytes: 80967
-    num_examples: 256
-  download_size: 28899321
-  dataset_size: 3773771
----
-
-# Dataset Card for ChrEn
-
-## Table of Contents
-- [Dataset Description](#dataset-description)
-  - [Dataset Summary](#dataset-summary)
-  - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
-  - [Languages](#languages)
-- [Dataset Structure](#dataset-structure)
-  - [Data Instances](#data-instances)
-  - [Data Fields](#data-fields)
-  - [Data Splits](#data-splits)
-- [Dataset Creation](#dataset-creation)
-  - [Curation Rationale](#curation-rationale)
-  - [Source Data](#source-data)
-  - [Annotations](#annotations)
-  - [Personal and Sensitive Information](#personal-and-sensitive-information)
-- [Considerations for Using the Data](#considerations-for-using-the-data)
-  - [Social Impact of Dataset](#social-impact-of-dataset)
-  - [Discussion of Biases](#discussion-of-biases)
-  - [Other Known Limitations](#other-known-limitations)
-- [Additional Information](#additional-information)
-  - [Dataset Curators](#dataset-curators)
-  - [Licensing Information](#licensing-information)
-  - [Citation Information](#citation-information)
-  - [Contributions](#contributions)
-
-## Dataset Description
-
-- **Repository:** [Github repository for ChrEn](https://github.com/ZhangShiyue/ChrEn)
-- **Paper:** [ChrEn: Cherokee-English Machine Translation for Endangered Language Revitalization](https://arxiv.org/abs/2010.04791)
-- **Point of Contact:** [[email protected]]([email protected])
-
-### Dataset Summary
-
-ChrEn is a Cherokee-English parallel dataset to facilitate machine translation research between Cherokee and English.
-ChrEn is extremely low-resource contains 14k sentence pairs in total, split in ways that facilitate both in-domain and out-of-domain evaluation.
-ChrEn also contains 5k Cherokee monolingual data to enable semi-supervised learning.
-
-### Supported Tasks and Leaderboards
-
-The dataset is intended to use for `machine-translation` between Enlish (`en`) and Cherokee (`chr`).
-
-### Languages
-
-The dataset contains Enlish (`en`) and Cherokee (`chr`) text. The data encompasses both existing dialects of Cherokee: the Overhill dialect, mostly spoken in Oklahoma (OK), and the Middle dialect, mostly used in North Carolina (NC).
-
-## Dataset Structure
-
-### Data Instances
-
-[More Information Needed]
-
-### Data Fields
-
-[More Information Needed]
-
-### Data Splits
-
-[More Information Needed]
-
-## Dataset Creation
-
-### Curation Rationale
-
-[More Information Needed]
-
-### Source Data
-
-#### Initial Data Collection and Normalization
-
-Many of the source texts were translations of English materials, which means that the Cherokee structures may not be 100% natural in terms of what a speaker might spontaneously produce. Each text was translated by people who speak Cherokee as the first language, which means there is a high probability of grammaticality. These data were originally available in PDF version. We apply the Optical Character Recognition (OCR) via Tesseract OCR engine to extract the Cherokee and English text.
-
-#### Who are the source language producers?
-
-[More Information Needed]
-
-### Annotations
-
-#### Annotation process
-
-[More Information Needed]
-
-#### Who are the annotators?
-
-The sentences were manually aligned by Dr. Benjamin Frey a proficient second-language speaker of Cherokee, who also fixed the errors introduced by OCR. This process is time-consuming and took several months.
-
-### Personal and Sensitive Information
-
-[More Information Needed]
-
-## Considerations for Using the Data
-
-### Social Impact of Dataset
-
-[More Information Needed]
-
-### Discussion of Biases
-
-[More Information Needed]
-
-### Other Known Limitations
-
-[More Information Needed]
-
-## Additional Information
-
-### Dataset Curators
-
-The dataset was gathered and annotated by Shiyue Zhang, Benjamin Frey, and Mohit Bansal at UNC Chapel Hill.
-
-### Licensing Information
-
-The copyright of the data belongs to original book/article authors or translators (hence, used for research purpose; and please contact Dr. Benjamin Frey for other copyright questions).
-
-### Citation Information
-
-```
-@inproceedings{zhang2020chren,
-  title={ChrEn: Cherokee-English Machine Translation for Endangered Language Revitalization},
-  author={Zhang, Shiyue and Frey, Benjamin and Bansal, Mohit},
-  booktitle={EMNLP2020},
-  year={2020}
-}
-```
-
-### Contributions
-
-Thanks to [@yjernite](https://github.com/yjernite), [@lhoestq](https://github.com/lhoestq) for adding this dataset.

chr_en.py

@@ -1,202 +0,0 @@
-# coding=utf-8
-# Copyright 2020 The HuggingFace Datasets Authors and the current dataset script contributor.
-#
-# Licensed under the Apache License, Version 2.0 (the "License");
-# you may not use this file except in compliance with the License.
-# You may obtain a copy of the License at
-#
-#     http://www.apache.org/licenses/LICENSE-2.0
-#
-# Unless required by applicable law or agreed to in writing, software
-# distributed under the License is distributed on an "AS IS" BASIS,
-# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-# See the License for the specific language governing permissions and
-# limitations under the License.
-"""ChrEn: Cherokee-English Machine Translation data"""
-
-
-import openpyxl  # noqa: requires this pandas optional dependency for reading xlsx files
-import pandas as pd
-
-import datasets
-
-
-_CITATION = """\
-@inproceedings{zhang2020chren,
-  title={ChrEn: Cherokee-English Machine Translation for Endangered Language Revitalization},
-  author={Zhang, Shiyue and Frey, Benjamin and Bansal, Mohit},
-  booktitle={EMNLP2020},
-  year={2020}
-}
-"""
-
-_DESCRIPTION = """\
-ChrEn is a Cherokee-English parallel dataset to facilitate machine translation research between Cherokee and English.
-ChrEn is extremely low-resource contains 14k sentence pairs in total, split in ways that facilitate both in-domain and out-of-domain evaluation.
-ChrEn also contains 5k Cherokee monolingual data to enable semi-supervised learning.
-"""
-
-_HOMEPAGE = "https://github.com/ZhangShiyue/ChrEn"
-
-_LICENSE = ""
-
-_URLs = {
-    "monolingual_raw": "https://github.com/ZhangShiyue/ChrEn/raw/main/data/raw/monolingual_data.xlsx",
-    "parallel_raw": "https://github.com/ZhangShiyue/ChrEn/raw/main/data/raw/parallel_data.xlsx",
-    "monolingual_chr": "https://raw.githubusercontent.com/ZhangShiyue/ChrEn/main/data/monolingual/chr",
-    "monolingual_en5000": "https://raw.githubusercontent.com/ZhangShiyue/ChrEn/main/data/monolingual/en5000",
-    "monolingual_en10000": "https://raw.githubusercontent.com/ZhangShiyue/ChrEn/main/data/monolingual/en10000",
-    "monolingual_en20000": "https://raw.githubusercontent.com/ZhangShiyue/ChrEn/main/data/monolingual/en20000",
-    "monolingual_en50000": "https://raw.githubusercontent.com/ZhangShiyue/ChrEn/main/data/monolingual/en50000",
-    "monolingual_en100000": "https://raw.githubusercontent.com/ZhangShiyue/ChrEn/main/data/monolingual/en100000",
-    "parallel_train.chr": "https://github.com/ZhangShiyue/ChrEn/raw/main/data/parallel/train.chr",
-    "parallel_train.en": "https://github.com/ZhangShiyue/ChrEn/raw/main/data/parallel/train.en",
-    "parallel_dev.chr": "https://github.com/ZhangShiyue/ChrEn/raw/main/data/parallel/dev.chr",
-    "parallel_dev.en": "https://github.com/ZhangShiyue/ChrEn/raw/main/data/parallel/dev.en",
-    "parallel_out_dev.chr": "https://github.com/ZhangShiyue/ChrEn/raw/main/data/parallel/out_dev.chr",
-    "parallel_out_dev.en": "https://github.com/ZhangShiyue/ChrEn/raw/main/data/parallel/out_dev.en",
-    "parallel_test.chr": "https://github.com/ZhangShiyue/ChrEn/raw/main/data/parallel/test.chr",
-    "parallel_test.en": "https://github.com/ZhangShiyue/ChrEn/raw/main/data/parallel/test.en",
-    "parallel_out_test.chr": "https://github.com/ZhangShiyue/ChrEn/raw/main/data/parallel/out_test.chr",
-    "parallel_out_test.en": "https://github.com/ZhangShiyue/ChrEn/raw/main/data/parallel/out_test.en",
-}
-
-
-# TODO: Name of the dataset usually match the script name with CamelCase instead of snake_case
-class ChrEn(datasets.GeneratorBasedBuilder):
-    """ChrEn: Cherokee-English Machine Translation data."""
-
-    VERSION = datasets.Version("1.0.0")
-
-    BUILDER_CONFIGS = [
-        datasets.BuilderConfig(name="monolingual_raw", version=VERSION, description="Monolingual data with metadata"),
-        datasets.BuilderConfig(name="parallel_raw", version=VERSION, description="Parallel data with metadata"),
-        datasets.BuilderConfig(name="monolingual", version=VERSION, description="Monolingual data text only"),
-        datasets.BuilderConfig(
-            name="parallel", version=VERSION, description="Parallel data text pairs only with default split"
-        ),
-    ]
-
-    DEFAULT_CONFIG_NAME = (
-        "parallel"  # It's not mandatory to have a default configuration. Just use one if it make sense.
-    )
-
-    def _info(self):
-        if (
-            self.config.name == "monolingual_raw"
-        ):  # This is the name of the configuration selected in BUILDER_CONFIGS above
-            features = datasets.Features(
-                {
-                    "text_sentence": datasets.Value("string"),
-                    "text_title": datasets.Value("string"),
-                    "speaker": datasets.Value("string"),
-                    "date": datasets.Value("int32"),
-                    "type": datasets.Value("string"),
-                    "dialect": datasets.Value("string"),
-                }
-            )
-        elif (
-            self.config.name == "parallel_raw"
-        ):  # This is the name of the configuration selected in BUILDER_CONFIGS above
-            features = datasets.Features(
-                {
-                    "line_number": datasets.Value("string"),  # doesn't always map to a number
-                    "sentence_pair": datasets.Translation(languages=["en", "chr"]),
-                    "text_title": datasets.Value("string"),
-                    "speaker": datasets.Value("string"),
-                    "date": datasets.Value("int32"),
-                    "type": datasets.Value("string"),
-                    "dialect": datasets.Value("string"),
-                }
-            )
-        elif (
-            self.config.name == "parallel"
-        ):  # This is an example to show how to have different features for "first_domain" and "second_domain"
-            features = datasets.Features(
-                {
-                    "sentence_pair": datasets.Translation(languages=["en", "chr"]),
-                }
-            )
-        elif (
-            self.config.name == "monolingual"
-        ):  # This is an example to show how to have different features for "first_domain" and "second_domain"
-            features = datasets.Features(
-                {
-                    "sentence": datasets.Value("string"),
-                }
-            )
-        return datasets.DatasetInfo(
-            description=_DESCRIPTION,
-            features=features,  # Here we define them above because they are different between the two configurations
-            supervised_keys=None,
-            homepage=_HOMEPAGE,
-            license=_LICENSE,
-            citation=_CITATION,
-        )
-
-    def _split_generators(self, dl_manager):
-        """Returns SplitGenerators."""
-        data_dir = dl_manager.download(_URLs)
-        if self.config.name in [
-            "monolingual_raw",
-            "parallel_raw",
-        ]:  # This is the name of the configuration selected in BUILDER_CONFIGS above
-            return [
-                datasets.SplitGenerator(
-                    name="full",
-                    gen_kwargs={
-                        "filepaths": data_dir,
-                        "split": "full",
-                    },
-                )
-            ]
-        elif self.config.name == "monolingual":
-            return [
-                datasets.SplitGenerator(
-                    name=spl,
-                    gen_kwargs={
-                        "filepaths": data_dir,
-                        "split": spl,
-                    },
-                )
-                for spl in ["chr", "en5000", "en10000", "en20000", "en50000", "en100000"]
-            ]
-        else:
-            return [
-                datasets.SplitGenerator(
-                    name=spl,
-                    gen_kwargs={
-                        "filepaths": data_dir,
-                        "split": spl,
-                    },
-                )
-                for spl in ["train", "dev", "out_dev", "test", "out_test"]
-            ]
-
-    def _generate_examples(self, filepaths, split):
-        if self.config.name == "monolingual_raw":
-            keys = ["text_sentence", "text_title", "speaker", "date", "type", "dialect"]
-            with open(filepaths["monolingual_raw"], "rb") as f:
-                monolingual = pd.read_excel(f, engine="openpyxl")
-                for id_, row in enumerate(monolingual.itertuples()):
-                    yield id_, dict(zip(keys, row[1:]))
-        elif self.config.name == "parallel_raw":
-            keys = ["line_number", "en_sent", "chr_sent", "text_title", "speaker", "date", "type", "dialect"]
-            with open(filepaths["parallel_raw"], "rb") as f:
-                parallel = pd.read_excel(f, engine="openpyxl")
-                for id_, row in enumerate(parallel.itertuples()):
-                    res = dict(zip(keys, row[1:]))
-                    res["sentence_pair"] = {"en": res["en_sent"], "chr": res["chr_sent"]}
-                    res["line_number"] = str(res["line_number"])
-                    del res["en_sent"]
-                    del res["chr_sent"]
-                    yield id_, res
-        elif self.config.name == "monolingual":
-            f = open(filepaths[f"monolingual_{split}"], encoding="utf-8")
-            for id_, line in enumerate(f):
-                yield id_, {"sentence": line.strip()}
-        elif self.config.name == "parallel":
-            fi = open(filepaths[f"parallel_{split}.en"], encoding="utf-8")
-            fo = open(filepaths[f"parallel_{split}.chr"], encoding="utf-8")
-            for id_, (line_en, line_chr) in enumerate(zip(fi, fo)):
-                yield id_, {"sentence_pair": {"en": line_en.strip(), "chr": line_chr.strip()}}

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