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README.md
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- copy-paste the tags obtained with the tagging app: https://github.com/huggingface/datasets-tagging
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---
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# Dataset Card for
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## Table of Contents
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- [Table of Contents](#table-of-contents)
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## Dataset Description
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- **Homepage:** https://
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- **Repository:**
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- **Paper:**
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- **Leaderboard:**
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### Dataset Summary
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About 300 speakers participated in the recording and conducted face-to-face communication in a natural way. They had free discussion on a number of given topics, with a wide range of fields; the voice was natural and fluent, in line with the actual dialogue scene. Text is transferred manually, with high accuracy.
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For more details, please refer to the link: https://
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### Supported Tasks and Leaderboards
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automatic-speech-recognition, audio-speaker-identification: The dataset can be used to train a model for Automatic Speech Recognition (ASR).
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- copy-paste the tags obtained with the tagging app: https://github.com/huggingface/datasets-tagging
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# Dataset Card for Nexdata/German_Conversational_Speech_Data_by_Mobile_Phone
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## Table of Contents
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- [Table of Contents](#table-of-contents)
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## Dataset Description
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- **Homepage:** https://www.nexdata.ai/datasets/1121?source=Huggingface
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- **Repository:**
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- **Paper:**
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- **Leaderboard:**
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### Dataset Summary
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About 300 speakers participated in the recording and conducted face-to-face communication in a natural way. They had free discussion on a number of given topics, with a wide range of fields; the voice was natural and fluent, in line with the actual dialogue scene. Text is transferred manually, with high accuracy.
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For more details, please refer to the link: https://www.nexdata.ai/datasets/1121?source=Huggingface
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### Supported Tasks and Leaderboards
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automatic-speech-recognition, audio-speaker-identification: The dataset can be used to train a model for Automatic Speech Recognition (ASR).
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