Large-Scale Voice Recognition Data for Advanced Models
In the forefront of artificial intelligence, large models, such as those based on deep learning architectures, require vast amounts of data to achieve exceptional performance. Our Large-Scale Voice Recognition Data is meticulously curated to provide the extensive and diverse dataset necessary for training these sophisticated models, enabling breakthroughs in voice recognition technology.
- Massive Data Volume: Our database contains billions of voice samples and millions of hours data, ensuring ample data to train and fine-tune large models for optimal accuracy.
- Wide-Ranging Diversity: Includes voice samples from speakers of various ages, genders, ethnicities, and accents, covering hundreds of languages and dialects to support global applications.
- High-Fidelity Recordings: Each sample is recorded in high-quality environments, ensuring clear and precise audio that enhances model training.
- Varied Contexts: The data encompasses a broad spectrum of contexts, including conversational speech, commands, narrative passages, and spontaneous dialogue.
- Detailed Annotations: Comprehensive metadata and annotations accompany each sample, including phonetic transcriptions, timestamps, speaker demographics, and environmental context.
Development
Improvement
We have all kinds of audio classification dataset,for example speech command dataset, common voice dataset.Beside this there is North American voice dataset,African sound dataset，Asian audio datasets，European voices dataset.
- Indoor
- Outdoor
- text
- Studio
- Incar
- Mobile (iOS/Android)
- Computer (Desktop/Laptop)
- Pro (Hi-Fi recorder/Mic Array)
- Language: Chinese / English / French / German…
- Gender balanced: 1:1
- Age: Children/Senior
- Education Background
annotate
transcribe / Validate
human & machine
Surfing Tech applies its own algorithm during speech dataset annotation to ensure high efficiency and accuracy. We achieve above 95% accuracy rate after three rounds of quality inspection, which makes the audio datasets more valuable for speech emotion recognition dataset, semantic understanding, and human-computer interaction.
- Over 30,000 hours of voice dataset collection
- Multi-region audio datasets： Australia, North America, South America, Europe, Asia
- Children mandarin speech emotion dataset 3-12 years
- Adult audio dataset Senior Mandarin: 800 speakers
- We have speech emotion recognition dataset in various regional dialects
- Such as Hakka, English dialects,Hindi voice data, etc.
- Central China: 1,000 speakers
- Indoor voice dataset,Customer service voice dataset
- Work environment speech dataset
- English voice dataest: North American, Australian, Singapores
- Multilingual voice data:Swahili speech data
- Russian speech dataest，French voices dataset
- Singaporean English,Kazakh speech dataests