| --- |
| pretty_name: VIVOS |
| annotations_creators: |
| - expert-generated |
| language_creators: |
| - crowdsourced |
| - expert-generated |
| language: |
| - vi |
| license: |
| - cc-by-nc-sa-4.0 |
| multilinguality: |
| - monolingual |
| size_categories: |
| - 10K<n<100K |
| source_datasets: |
| - original |
| task_categories: |
| - automatic-speech-recognition |
| task_ids: [] |
| dataset_info: |
| features: |
| - name: speaker_id |
| dtype: string |
| - name: path |
| dtype: string |
| - name: audio |
| dtype: |
| audio: |
| sampling_rate: 16000 |
| - name: sentence |
| dtype: string |
| splits: |
| - name: train |
| num_bytes: 1722002133 |
| num_examples: 11660 |
| - name: test |
| num_bytes: 86120227 |
| num_examples: 760 |
| download_size: 1475540500 |
| dataset_size: 1808122360 |
| --- |
| |
| # Dataset Card for VIVOS |
|
|
| ## Table of Contents |
| - [Dataset Card for VIVOS](#dataset-card-for-vivos) |
| - [Table of Contents](#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) |
| - [Initial Data Collection and Normalization](#initial-data-collection-and-normalization) |
| - [Who are the source language producers?](#who-are-the-source-language-producers) |
| - [Annotations](#annotations) |
| - [Annotation process](#annotation-process) |
| - [Who are the annotators?](#who-are-the-annotators) |
| - [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 |
|
|
| - **Homepage:** https://doi.org/10.5281/zenodo.7068130 |
| - **Repository:** [Needs More Information] |
| - **Paper:** [A non-expert Kaldi recipe for Vietnamese Speech Recognition System](https://aclanthology.org/W16-5207/) |
| - **Leaderboard:** [Needs More Information] |
| - **Point of Contact:** [AILAB](mailto:ailab@hcmus.edu.vn) |
|
|
| ### Dataset Summary |
|
|
| VIVOS is a free Vietnamese speech corpus consisting of 15 hours of recording speech prepared for Vietnamese Automatic Speech Recognition task. |
|
|
| The corpus was prepared by AILAB, a computer science lab of VNUHCM - University of Science, with Prof. Vu Hai Quan is the head of. |
|
|
| We publish this corpus in hope to attract more scientists to solve Vietnamese speech recognition problems. |
|
|
| ### Supported Tasks and Leaderboards |
|
|
| [Needs More Information] |
|
|
| ### Languages |
|
|
| Vietnamese |
|
|
| ## Dataset Structure |
|
|
| ### Data Instances |
|
|
| A typical data point comprises the path to the audio file, called `path` and its transcription, called `sentence`. Some additional information about the speaker and the passage which contains the transcription is provided. |
|
|
| ``` |
| {'speaker_id': 'VIVOSSPK01', |
| 'path': '/home/admin/.cache/huggingface/datasets/downloads/extracted/b7ded9969e09942ab65313e691e6fc2e12066192ee8527e21d634aca128afbe2/vivos/train/waves/VIVOSSPK01/VIVOSSPK01_R001.wav', |
| 'audio': {'path': '/home/admin/.cache/huggingface/datasets/downloads/extracted/b7ded9969e09942ab65313e691e6fc2e12066192ee8527e21d634aca128afbe2/vivos/train/waves/VIVOSSPK01/VIVOSSPK01_R001.wav', |
| 'array': array([-0.00048828, -0.00018311, -0.00137329, ..., 0.00079346, 0.00091553, 0.00085449], dtype=float32), |
| 'sampling_rate': 16000}, |
| 'sentence': 'KHÁCH SẠN'} |
| ``` |
|
|
| ### Data Fields |
|
|
| - speaker_id: An id for which speaker (voice) made the recording |
| |
| - path: The path to the audio file |
| |
| - audio: A dictionary containing the path to the downloaded audio file, the decoded audio array, and the sampling rate. 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]`. |
|
|
| - sentence: The sentence the user was prompted to speak |
|
|
| ### Data Splits |
|
|
| The speech material has been subdivided into portions for train and test. |
|
|
| Speech was recorded in a quiet environment with high quality microphone, speakers were asked to read one sentence at a time. |
|
|
| | | Train | Test | |
| | ---------------- | ----- | ----- | |
| | Speakers | 46 | 19 | |
| | Utterances | 11660 | 760 | |
| | Duration | 14:55 | 00:45 | |
| | Unique Syllables | 4617 | 1692 | |
|
|
| ## Dataset Creation |
|
|
| ### Curation Rationale |
|
|
| [Needs More Information] |
|
|
| ### Source Data |
|
|
| #### Initial Data Collection and Normalization |
|
|
| [Needs More Information] |
|
|
| #### Who are the source language producers? |
|
|
| [Needs More Information] |
|
|
| ### Annotations |
|
|
| #### Annotation process |
|
|
| [Needs More Information] |
|
|
| #### Who are the annotators? |
|
|
| [Needs More Information] |
|
|
| ### Personal and Sensitive Information |
|
|
| The dataset consists of people who have donated their voice online. You agree to not attempt to determine the identity of speakers in this dataset. |
|
|
| ## Considerations for Using the Data |
|
|
| ### Social Impact of Dataset |
|
|
| [More Information Needed] |
|
|
| ### Discussion of Biases |
|
|
| [More Information Needed] |
|
|
| ### Other Known Limitations |
|
|
| Dataset provided for research purposes only. Please check dataset license for additional information. |
|
|
| ## Additional Information |
|
|
| ### Dataset Curators |
|
|
| The dataset was initially prepared by AILAB, a computer science lab of VNUHCM - University of Science. |
|
|
| ### Licensing Information |
|
|
| Public Domain, Creative Commons Attribution NonCommercial ShareAlike v4.0 ([CC BY-NC-SA 4.0](https://creativecommons.org/licenses/by-nc-sa/4.0/legalcode)) |
|
|
| ### Citation Information |
|
|
| ``` |
| @inproceedings{luong-vu-2016-non, |
| title = "A non-expert {K}aldi recipe for {V}ietnamese Speech Recognition System", |
| author = "Luong, Hieu-Thi and |
| Vu, Hai-Quan", |
| booktitle = "Proceedings of the Third International Workshop on Worldwide Language Service Infrastructure and Second Workshop on Open Infrastructures and Analysis Frameworks for Human Language Technologies ({WLSI}/{OIAF}4{HLT}2016)", |
| month = dec, |
| year = "2016", |
| address = "Osaka, Japan", |
| publisher = "The COLING 2016 Organizing Committee", |
| url = "https://aclanthology.org/W16-5207", |
| pages = "51--55", |
| } |
| ``` |
|
|
| ### Contributions |
|
|
| Thanks to [@binh234](https://github.com/binh234) for adding this dataset. |
