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README.md

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+
+---
+license: cc-by-sa-4.0
+language: 
+- tha
+pretty_name: Thai Elderly Speech
+task_categories: 
+- speech-to-text-translation
+tags: 
+- speech-to-text-translation
+---
+
+The Thai Elderly Speech dataset by Data Wow and VISAI Version 1 dataset aims at
+advancing Automatic Speech Recognition (ASR) technology specifically for the
+elderly population. Researchers can use this dataset to advance ASR technology
+for healthcare and smart home applications. The dataset consists of 19,200 audio
+files, totaling 17 hours and 11 minutes of recorded speech. The files are
+divided into 2 categories: Healthcare (relating to medical issues and services
+in 30 medical categories) and Smart Home (relating to smart home devices in 7
+household contexts). The dataset contains 5,156 unique sentences spoken by 32
+seniors (10 males and 22 females), aged 57-60 years old (average age of 63
+years).
+
+
+## Languages
+
+tha
+
+## Supported Tasks
+
+Speech To Text Translation
+    
+## Dataset Usage
+### Using `datasets` library
+```
+    from datasets import load_dataset
+    dset = datasets.load_dataset("SEACrowd/thai_elderly_speech", trust_remote_code=True)
+```
+### Using `seacrowd` library
+```import seacrowd as sc
+# Load the dataset using the default config
+    dset = sc.load_dataset("thai_elderly_speech", schema="seacrowd")
+# Check all available subsets (config names) of the dataset
+    print(sc.available_config_names("thai_elderly_speech"))
+# Load the dataset using a specific config
+    dset = sc.load_dataset_by_config_name(config_name="<config_name>")
+```
+    
+    More details on how to load the `seacrowd` library can be found [here](https://github.com/SEACrowd/seacrowd-datahub?tab=readme-ov-file#how-to-use).
+    
+
+## Dataset Homepage
+
+[https://github.com/VISAI-DATAWOW/Thai-Elderly-Speech-dataset/releases/tag/v1.0.0](https://github.com/VISAI-DATAWOW/Thai-Elderly-Speech-dataset/releases/tag/v1.0.0)
+
+## Dataset Version
+
+Source: 1.0.0. SEACrowd: 2024.06.20.
+
+## Dataset License
+
+Creative Commons Attribution Share Alike 4.0 (cc-by-sa-4.0)
+
+## Citation
+
+If you are using the **Thai Elderly Speech** dataloader in your work, please cite the following:
+```
+
+
+@article{lovenia2024seacrowd,
+    title={SEACrowd: A Multilingual Multimodal Data Hub and Benchmark Suite for Southeast Asian Languages}, 
+    author={Holy Lovenia and Rahmad Mahendra and Salsabil Maulana Akbar and Lester James V. Miranda and Jennifer Santoso and Elyanah Aco and Akhdan Fadhilah and Jonibek Mansurov and Joseph Marvin Imperial and Onno P. Kampman and Joel Ruben Antony Moniz and Muhammad Ravi Shulthan Habibi and Frederikus Hudi and Railey Montalan and Ryan Ignatius and Joanito Agili Lopo and William Nixon and Börje F. Karlsson and James Jaya and Ryandito Diandaru and Yuze Gao and Patrick Amadeus and Bin Wang and Jan Christian Blaise Cruz and Chenxi Whitehouse and Ivan Halim Parmonangan and Maria Khelli and Wenyu Zhang and Lucky Susanto and Reynard Adha Ryanda and Sonny Lazuardi Hermawan and Dan John Velasco and Muhammad Dehan Al Kautsar and Willy Fitra Hendria and Yasmin Moslem and Noah Flynn and Muhammad Farid Adilazuarda and Haochen Li and Johanes Lee and R. Damanhuri and Shuo Sun and Muhammad Reza Qorib and Amirbek Djanibekov and Wei Qi Leong and Quyet V. Do and Niklas Muennighoff and Tanrada Pansuwan and Ilham Firdausi Putra and Yan Xu and Ngee Chia Tai and Ayu Purwarianti and Sebastian Ruder and William Tjhi and Peerat Limkonchotiwat and Alham Fikri Aji and Sedrick Keh and Genta Indra Winata and Ruochen Zhang and Fajri Koto and Zheng-Xin Yong and Samuel Cahyawijaya},
+    year={2024},
+    eprint={2406.10118},
+    journal={arXiv preprint arXiv: 2406.10118}
+}
+
+```