Commercial

Human-Robot Conversation Dataset (German)

Human-Robot Conversation Dataset (German) 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.

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  • Hours
    660+
  • Files
    20,000
human robot dialogue german
  • Voice Assistant
  • ASR
  • Machine Learning
  • Audio Processing
  • Voice Recognition

Human-Robot Conversation Dataset (German) 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.

Get in touch Download sample
  • Voice Assistant
  • ASR
  • Machine Learning
  • Audio Processing
  • Voice Recognition
  • Hours
    660+
  • Files
    20,000

Dataset Info

Characteristic Data
Description Audio of German dialogues between AI and humans
Data types Audio
Tasks Speech Recognition, LLM
Hours of audio 660+
Number of sets 20,000
Language German
Labeling Metadata (id, language, format)
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Technical
Characteristics

Characteristic Data
Audio Format M4A, WAV
Duration Max = 2 min
Source and collection methodology: Data was collected via crowdsourcing platforms.

Dataset Use Cases

  • Robotics & Human–Robot Interaction

    Training Human-Robot Dialogue Systems

    This human-robot dataset contains German conversations between artificial agents and humans recorded in natural interaction scenarios. The audio dataset supports machine learning models used in robotic systems that understand spoken instructions and responses. Researchers train conversational agents and language models for human-robot collaboration in service robots and social robotics environments.

  • Speech Technology & Language Processing

    Speech Recognition for Human-Robot Communication

    Developers use this German conversation audio dataset to train speech recognition systems designed for human-robot communication. The dialogue dataset contains natural spoken German from multiple speakers and short conversation sessions. Models trained on this training data improve speech recognition accuracy, spoken language processing, and voice interaction in conversational AI systems.

  • Artificial Intelligence & Conversational Agents

    Training Language Models

    The dataset provides training data for language models designed to generate and understand German dialogue. Multiple conversations between humans and artificial agents help models learn sentence structure, conversational context, and response patterns. These datasets support conversational agents used in virtual assistants, robotics platforms, and automated dialogue systems.

  • Social Robotics & Human-Centered AI

    Analyzing Social Interaction in Human-Robot Conversations

    Researchers use this dialogue dataset to study social interactions between humans and robots in spoken communication scenarios. The dataset comprising thousands of German recordings enables pattern analysis of dialogue flow, emotions, and interaction behaviors. Such data supports emotion recognition, human-robot collaboration studies, and the development of socially aware robotic systems.

FAQs

What is included in Human-Robot Conversation Dataset (German)?
The dataset comprises more than 660 hours of German conversation recordings across approximately 20,000 dialogue files. Each recording contains spoken interactions between humans and AI systems, providing extensive training data for machine learning models.
What types of annotations are provided in the dataset?
Each audio file includes structured metadata annotations, including file ID, language, and audio format. These annotations help organize the dataset and support efficient data analysis, training dataset preparation, and model evaluation.
What audio formats and technical characteristics are included?
The dataset includes audio recordings in M4A and WAV formats with a maximum duration of approximately two minutes per dialogue file. These standardized formats make the dataset suitable for speech datasets, language processing pipelines, and conversational AI development.
How was the human-robot conversation data collected?
Data was collected through crowdsourcing platforms where participants recorded dialogues simulating human-robot interactions in the German language. This process enables large-scale data collection with varied conversation patterns and realistic speech scenarios.
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After submitting a request, the Unidata team reviews the details and completes the required documentation. Once the agreement is signed and payment is processed, the dataset is delivered within 3–10 days.
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