The Thai Speech Dataset offers an extensive collection of authentic audio recordings from native Thai speakers across Thailand. This specialized dataset comprises 184 hours of carefully curated Thai speech professionally recorded and annotated for advanced machine learning applications.
Thai, spoken by over 60 million people as official language of Thailand with distinctive tonal system, is captured with phonological features essential for developing robust speech recognition systems serving Southeast Asian markets and Thai-speaking populations.
Dataset General Info
| Parameter | Details |
| Size | 184 hours |
| Format | MP3/WAV |
| Tasks | Speech recognition, AI training, voice assistant development, natural language processing, acoustic modeling, speaker identification |
| File size | 389 MB |
| Number of files | 741 files |
| Gender of speakers | Female: 49%, Male: 51% |
| Age of speakers | 18-30 years: 28%, 31-40 years: 30%, 40-50 years: 25%, 50+ years: 17% |
| Countries | Thailand |
Use Cases
National Digital Economy: Thai government agencies and technology companies can utilize the Thai Speech Dataset to develop voice-enabled digital services, e-commerce platforms, and smart city solutions across Thailand. Voice interfaces in Thai support Thailand’s digital economy initiatives, make services accessible to 60+ million Thai speakers, enable voice-based transactions and services, and position Thailand competitively in Southeast Asian technology markets. Applications include government digital services, banking voice interfaces, e-commerce platforms from Thai startups, smart city infrastructure in Bangkok, and digital services supporting Thailand’s growing technology sector.
Tourism and Hospitality Industry: Thailand’s vital tourism industry can leverage this dataset to create voice-guided tours, multilingual hospitality services, and tourism information platforms in Thai. Voice technology enhances experiences for domestic Thai tourists and promotes Thai language internationally, supports hospitality sector serving tens of millions of annual visitors, enables voice-based hotel services and tour bookings, and facilitates tourism in country welcoming visitors from worldwide. Applications include temple tour guides, cultural heritage apps for Ayutthaya and Sukhothai, hotel voice assistants, restaurant services, and tourism platforms.
Healthcare and Traditional Medicine: Healthcare providers across Thailand can employ this dataset to develop voice-enabled health information systems, telemedicine platforms, and medical education tools in Thai. Voice technology improves healthcare accessibility, supports traditional Thai medicine integration with modern healthcare, enables remote patient monitoring in rural areas, and facilitates health education. Applications include health hotlines, hospital information systems, telemedicine consultations, traditional medicine guidance, pharmaceutical information, and public health campaigns serving Thailand’s population with distinctive tonal Thai language requirements.
FAQ
Q: What is included in this dataset?
A: The dataset includes 184 hours of audio recordings with 741 files totaling 389 MB, complete with transcriptions and linguistic annotations.
Q: How diverse is the speaker demographic?
A: Features 49% female and 51% male speakers across age groups: 28% (18-30), 30% (31-40), 25% (40-50), 17% (50+).
How to Use the Speech Dataset
Step 1: Dataset Acquisition – Download the dataset package from the provided link upon purchase.
Step 2: Extract and Organize – Extract to your storage and review the structured folder organization.
Step 3: Environment Setup – Install ML framework dependencies and audio processing libraries.
Step 4: Data Preprocessing – Load audio files and apply preprocessing steps like resampling and feature extraction.
Step 5: Model Training – Split into training/validation/test sets and train your model.
Step 6: Evaluation and Fine-tuning – Evaluate performance and iterate on architecture.
Step 7: Deployment – Export and integrate your trained model into production systems.
For comprehensive documentation, refer to included guides.
