Create README.md

README.md

@@ -0,0 +1,73 @@
+---
+language:
+- ko
+language_creators:
+- crowdsourced
+license:
+- cc-by-4.0
+multilinguality:
+- monolingual
+pretty_name: zeroth-korean
+size_categories:
+- 10K<n<100K
+task_categories:
+- automatic-speech-recognition
+---
+# Zeroth-Korean
+## Dataset Description
+- **Homepage:** [OpenSLR](https://www.openslr.org/40/)
+- **Repository:** [goodatlas/zeroth](https://github.com/goodatlas/zeroth)
+- **Download Size** 2.68 GiB
+- **Generated Size** 2.85 GiB
+- **Total Size** 5.52 GiB
+
+## Zeroth-Korean
+
+The data set contains transcriebed audio data for Korean. There are 51.6 hours transcribed Korean audio for training data (22,263 utterances, 105 people, 3000 sentences) and 1.2 hours transcribed Korean audio for testing data (457 utterances, 10 people). This corpus also contains pre-trained/designed language model, lexicon and morpheme-based segmenter(morfessor).
+Zeroth project introduces free Korean speech corpus and aims to make Korean speech recognition more broadly accessible to everyone.
+This project was developed in collaboration between Lucas Jo(@Atlas Guide Inc.) and Wonkyum Lee(@Gridspace Inc.).
+
+Contact: Lucas Jo([email protected]), Wonkyum Lee([email protected])
+
+### License
+CC BY 4.0
+
+## Dataset Structure
+
+### Data Instance
+
+```pycon
+>>> from datasets import load_dataset
+>>> dataset = load_dataset("Bingsu/zeroth-korean")
+>>> dataset
+DatasetDict({
+    train: Dataset({
+        features: ['audio', 'text'],
+        num_rows: 22263
+    })
+    test: Dataset({
+        features: ['text', 'audio'],
+        num_rows: 457
+    })
+})
+```
+
+### Data Size
+
+download: 2.68 GiB<br>
+generated: 2.85 GiB<br>
+total: 5.52 GiB
+
+### Data Fields
+
+- audio: `audio`, sampling rate = 16000
+    - Note that when accessing the audio column: `dataset[0]["audio"]` the audio file is automatically decoded and resampled to `dataset.features["audio"].sampling_rate`. Decoding and resampling of a large number of audio files might take a significant amount of time. Thus it is important to first query the sample index before the "audio" column, i.e. `dataset[0]["audio"]` should always be preferred over `dataset["audio"][0]`.
+- text: `string`
+
+
+
+### Data Splits
+
+|            |   train  |  test |
+| ---------- | -------- | ----- |
+| # of data  |    22263 |   457 |