Speech Recognition Datasets

This 200 Hours Korean Full-Duplex Multi-Channel Speech Dataset features multi-stream audio recorded via smartphones, simulating natural conversations across a range of everyday topics. Each dialogue is annotated with transcripts, speaker ID, gender, and age. Collected from diverse speakers across various regions in Korea, the dataset enhances AI model robustness in real-world applications. Ideal for training automatic speech recognition (ASR), conversational AI, multilingual dialogue systems, and natural speech processing models. All data complies with GDPR, CCPA, and PIPL privacy standards, ensuring safe and ethical AI training.

This Korean Financial Speech Dataset contains 215 hours of real-world audio, including casual conversations and monologues. The content spans professional financial terminology in macroeconomics and microeconomics contexts, simulating authentic banking and financial service interactions. Each recording includes transcriptions, speaker metadata (ID, gender), and tagged financial entities. The dataset supports a wide range of AI applications such as automatic speech recognition (ASR), financial natural language understanding (NLU), voicebot development, and domain-specific language modeling. All data complies with GDPR, CCPA, and PIPL regulations, ensuring privacy and ethical usage.

This Korean Telephony Speech Dataset contains 136 hours of spontaneous dialogue recorded over phone calls. Covering over 20 real-life domains including customer service, e-commerce, finance, travel, and daily conversations, the dataset features natural two-speaker conversations collected via diverse telephony channels. Each sample is transcribed and annotated with speaker ID, gender, age, and other metadata. Data was collected from 216 native Korean speakers across different regions, enhancing model generalization. Ideal for automatic speech recognition (ASR), speaker diarization, and call center conversational AI systems. All data complies with GDPR, CCPA, and PIPL for responsible and legal AI development.

This Korean Medical Speech Dataset contains 203 hours of real-world audio including casual conversations and monologues. It spans a wide range of healthcare-related content such as medical consultations, academic lectures, training sessions, and clinical discussions. The dataset includes detailed annotations: transcripts, speaker ID, gender, and tagged medical entities. Designed for use in ASR, medical NLU, speech-based healthcare assistants, and AI model fine-tuning for domain-specific speech recognition. The recordings were collected from a geographically diverse speaker base and validated by multiple AI companies. All data complies with GDPR, CCPA, and PIPL regulations.

This 393-hour Korean Children Speech Dataset consists of scripted monologue recordings from young speakers, captured using smartphones. The speech content includes essays, storytelling, and numeric readings. Each audio file is transcribed and annotated with metadata such as speaker ID, gender, and age. Collected from a geographically diverse group of native Korean-speaking children, this dataset is designed to support training of automatic speech recognition (ASR), text-to-speech (TTS), pronunciation evaluation systems, and educational language models. The dataset has been quality-verified by multiple AI enterprises and is fully compliant with GDPR, CCPA, and PIPL privacy regulations.

Korean(Korea) Real-world Casual Conversation and Monologue speech dataset, mirrors real-world interactions. Transcribed with text content, speaker's ID, gender, and other attributes. Our dataset was collected from extensive and diversify speakers, geographicly speaking, enhancing model performance in real and complex tasks. Quality tested by various AI companies. We strictly adhere to data protection regulations and privacy standards, ensuring the maintenance of user privacy and legal rights throughout the data collection, storage, and usage processes, our datasets are all GDPR, CCPA, PIPL complied.

Korean(Korea) Children Real-world Casual Conversation and Monologue speech dataset, covers self-media, conversation, live, lecture, variety show and other generic domains, mirrors real-world interactions. Transcribed with text content, speaker's ID, gender, age, accent and other attributes. Our dataset was collected from extensive and diversify speakers(12 years old and younger children), geographicly speaking, enhancing model performance in real and complex tasks. Quality tested by various AI companies. We strictly adhere to data protection regulations and privacy standards, ensuring the maintenance of user privacy and legal rights throughout the data collection, storage, and usage processes, our datasets are all GDPR, CCPA, PIPL complied.

Korean(Korea) Spontaneous Dialogue Smartphone speech dataset, collected from dialogues based on given topics, covering 20+ domains. Transcribed with text content, speaker's ID, gender, age and other attributes. Our dataset was collected from extensive and diversify speakers(442 native speakers), geographicly speaking, enhancing model performance in real and complex tasks. Quality tested by various AI companies. We strictly adhere to data protection regulations and privacy standards, ensuring the maintenance of user privacy and legal rights throughout the data collection, storage, and usage processes, our datasets are all GDPR, CCPA, PIPL complied.

Korean(Korea) Scripted Monologue Smartphone speech dataset, collected from monologue based on given scripts, covering generic domain, human-machine interaction, smart home command and control, in-car command and control, numbers and other domains. Transcribed with text content and other attributes. Our dataset was collected from extensive and diversify speakers(1,077 people in total), geographicly speaking, enhancing model performance in real and complex tasks. Quality tested by various AI companies. We strictly adhere to data protection regulations and privacy standards, ensuring the maintenance of user privacy and legal rights throughout the data collection, storage, and usage processes, our datasets are all GDPR, CCPA, PIPL complied.