Medical Conversations Dataset (English)

Human-robot dataset is an audio dataset containing 660+ hours of Korean dialogues between an AI and humans across 20,000 recordings. This conversation dataset includes short M4A and WAV audio files (up to 2 minutes) with structured metadata, supporting research in human-robot interactions, Korean natural language processing, and AI-driven dialogue systems.

Human-robot dataset is an audio dataset containing 660+ hours of Russian dialogues between an AI and humans across 20,000 recordings, created for training conversational AI, speech recognition systems, and language models. This conversation dataset includes short audio sessions (up to 2 minutes) in M4A and OGG formats with structured metadata.

Human-robot dataset is an audio dataset comprising 660+ hours of German dialogues between an AI and humans across 20,000 recordings, designed for training conversational agents, speech recognition systems, and language models. The conversation dataset includes short audio sessions (up to 2 minutes) in M4A and WAV formats with structured metadata.

Human-Robot dataset contains 660+ hours of audio featuring dialogues between AI and a human in English across 20,000 recordings. The dataset supports conversational AI, speech recognition, and human-robot interaction research, with short M4A audio files (up to 2 minutes) and structured metadata for model training.

Slovenian speech dataset contains over 10 hours of telephone-recorded dialogues from 20+ native speakers, delivered in MP3 and WAV formats with low background noise and minute-long segments. The dataset includes structured annotations (ID, language, format, duration), making it well-suited for Slovenian speech recognition, spoken language processing, and training language models built on high-quality continuous and spontaneous speech data.

Arabic speech dataset provides over 10 hours of telephone-quality dialogues recorded by 20+ native Arabic speakers from the UAE, offering clean, high-quality audio data suitable for training speech recognition systems, dialogue models, and Arabic language processing tools. The dataset contains annotated audio recordings (ID, language, format, duration) in M4A, MP3, WAV, and AAC, captured with low background noise.

Vietnamese speech dataset features over 10 hours of telephone-quality audio recordings from native Vietnamese speakers, providing a diverse speech corpus for recognition tasks and training data for NLP models. This Vietnamese audio dataset contains real conversational dialogues with detailed annotations, making it well-suited for machine learning, multi-dialect processing, and benchmarking speech-driven AI systems.

This Korean speech dataset provides over 10 hours of telephone-based dialogues recorded by native Korean speakers, offering clean audio data for speech recognition, NLP training, and conversational AI. This Korean audio dataset includes annotated files, consistent recording conditions, and varied dialogue samples, making it a reliable speech corpus for model training and real-world speech detection tasks.

High-quality professional illustrations dataset containing 30,000 images across 20 diverse artistic styles, including 3D, Cartoon, Caricature, Graffiti, and more. The annotated images dataset includes metadata on style, color, keywords, and plot, providing rich training data for image classification, style transfer, and creative machine learning applications.

This hair loss dataset provides alopecia images of women captured from the top and front sides, labeled into three classes based on the Ludwig scale, with metadata (age, gender, ethnicity) to support machine learning, deep learning, and AI models for hair loss detection, early diagnosis, and research on hair thinning and scalp health.