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--- |
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pretty_name: 'Snow Mountain' |
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configs: |
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- v0.01 |
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language: |
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- hi |
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- bgc |
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- kfs |
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- dgo |
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- bhd |
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- gbk |
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- xnr |
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- kfx |
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- mjl |
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- kfo |
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- bfz |
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- mal |
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annotations_creators: |
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- ? |
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language_creators: |
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- ? |
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license: [] |
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multilinguality: |
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- multilingual |
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size_categories: |
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- |
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source_datasets: |
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- Snow Mountain |
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tags: [] |
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task_categories: |
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- automatic-speech-recognition |
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task_ids: [] |
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configs: |
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- mal |
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dataset_info: |
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- config_name: mal |
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features: |
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- name: Unnamed |
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dtype: int64 |
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- name: sentence |
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dtype: string |
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- name: path |
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dtype: string |
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splits: |
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- name: train_500 |
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num_bytes: 1295622 |
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num_examples: 22 |
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- name: test_common |
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num_bytes: 411844 |
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num_examples: 9 |
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- name: val_500 |
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- name: train_1000 |
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num_bytes: 40023390 |
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num_examples: 752 |
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- name: val_1000 |
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num_bytes: 1707426 |
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num_examples: 31 |
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download_size: 41038412 |
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dataset_size: 43799908 |
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--- |
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# Dataset Card for [Dataset Name] |
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## Table of Contents |
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- [Table of Contents](#table-of-contents) |
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- [Dataset Description](#dataset-description) |
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- [Dataset Summary](#dataset-summary) |
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- [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards) |
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- [Languages](#languages) |
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- [Dataset Structure](#dataset-structure) |
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- [Data Instances](#data-instances) |
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- [Data Fields](#data-fields) |
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- [Data Splits](#data-splits) |
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- [Dataset Creation](#dataset-creation) |
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- [Curation Rationale](#curation-rationale) |
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- [Source Data](#source-data) |
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- [Annotations](#annotations) |
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- [Personal and Sensitive Information](#personal-and-sensitive-information) |
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- [Considerations for Using the Data](#considerations-for-using-the-data) |
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- [Social Impact of Dataset](#social-impact-of-dataset) |
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- [Discussion of Biases](#discussion-of-biases) |
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- [Other Known Limitations](#other-known-limitations) |
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- [Additional Information](#additional-information) |
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- [Dataset Curators](#dataset-curators) |
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- [Licensing Information](#licensing-information) |
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- [Citation Information](#citation-information) |
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- [Contributions](#contributions) |
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## Dataset Description |
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- **Homepage:** |
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- **Repository:https://gitlabdev.bridgeconn.com/software/research/datasets/snow-mountain** |
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- **Paper:https://arxiv.org/abs/2206.01205** |
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- **Leaderboard:** |
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- **Point of Contact:** |
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### Dataset Summary |
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The Snow Mountain dataset contains the audio recordings (in .mp3 format) and the corresponding text of The Bible in 11 Indian languages. The recordings were done in a studio setting by native speakers. Each language has a single speaker in the dataset. Most of these languages are geographically concentrated in the Northern part of India around the state of Himachal Pradesh. Being related to Hindi they all use the Devanagari script for transcription. |
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We have used this dataset for experiments in ASR tasks. But these could be used for other applications in speech domain, like speaker recognition, language identification or even as unlabelled corpus for pre-training. |
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### Supported Tasks and Leaderboards |
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Atomatic speech recognition, Speaker recognition, Language identification |
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### Languages |
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Hindi, Haryanvi, Bilaspuri, Dogri, Bhadrawahi, Gaddi, Kangri, Kulvi, Mandeali, Kulvi Outer Seraji, Pahari Mahasui |
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## Dataset Structure |
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### Data Instances |
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[More Information Needed] |
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### Data Fields |
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[More Information Needed] |
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### Data Splits |
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[More Information Needed] |
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## Dataset Creation |
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### Curation Rationale |
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[More Information Needed] |
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### Source Data |
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The Bible recordings were done in a studio setting by native speakers. |
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#### Initial Data Collection and Normalization |
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[More Information Needed] |
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#### Who are the source language producers? |
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[More Information Needed] |
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### Annotations |
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#### Annotation process |
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[More Information Needed] |
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#### Who are the annotators? |
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[More Information Needed] |
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### Personal and Sensitive Information |
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[More Information Needed] |
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## Considerations for Using the Data |
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### Social Impact of Dataset |
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[More Information Needed] |
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### Discussion of Biases |
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[More Information Needed] |
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### Other Known Limitations |
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[More Information Needed] |
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## Additional Information |
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### Dataset Curators |
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[More Information Needed] |
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### Licensing Information |
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[More Information Needed] |
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### Citation Information |
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@misc{https://doi.org/10.48550/arxiv.2206.01205, |
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doi = {10.48550/ARXIV.2206.01205}, |
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url = {https://arxiv.org/abs/2206.01205}, |
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author = {Raju, Kavitha and V, Anjaly and Lish, Ryan and Mathew, Joel}, |
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keywords = {Audio and Speech Processing (eess.AS), Machine Learning (cs.LG), Sound (cs.SD), FOS: Electrical engineering, electronic engineering, information engineering, FOS: Electrical engineering, electronic engineering, information engineering, FOS: Computer and information sciences, FOS: Computer and information sciences}, |
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title = {Snow Mountain: Dataset of Audio Recordings of The Bible in Low Resource Languages}, |
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publisher = {arXiv}, |
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year = {2022}, |
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copyright = {Creative Commons Attribution Share Alike 4.0 International} |
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} |
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### Contributions |
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Thanks to [@github-username](https://github.com/<github-username>) for adding this dataset. |
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