Datasets:
Improve CSEMOTIONS dataset card: Add metadata and links
Browse filesThis PR enhances the CSEMOTIONS dataset card by:
- Adding crucial metadata: `task_categories` (text-to-speech), `library_name` (datasets), `license` (apache-2.0), `language` (zh for Mandarin Chinese), and relevant `tags` (speech, emotional-speech, voice-cloning, mandarin).
- Including direct links to the associated paper ([Marco-Voice Technical Report](https://huggingface.co/papers/2508.02038)) and the project's GitHub repository ([AIDC-AI/Marco-Voice](https://github.com/AIDC-AI/Marco-Voice)) at the top of the dataset card for improved discoverability.
- Correcting the number of speakers in the "Dataset Summary" for consistency with the paper and "Dataset Details".
- Restructuring the card to place metadata at the very top, followed directly by Markdown content, in line with Hugging Face Hub best practices.
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dataset_info:
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features:
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splits:
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download_size: 3077432286
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dataset_size: 3610108297.64
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configs:
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---
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# CSEMOTIONS: High-Quality Mandarin Emotional Speech Dataset
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[](LICENSE)
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**CSEMOTIONS** is a high-quality Mandarin emotional speech dataset designed for expressive speech synthesis, emotion recognition, and voice cloning research. The dataset contains studio-quality recordings from six professional voice actors across seven carefully curated emotional categories, supporting research in controllable and natural language speech generation.
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- **Name:** CSEMOTIONS
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- **Total Duration:** ~10 hours
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- **Speakers:**
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- **Emotions:** Neutral, Happy, Angry, Sad, Surprise, Disgust, Fear
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- **Language:** Mandarin Chinese
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- **Sampling Rate:** 48kHz, 24-bit PCM
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We used compliance checking algorithms during the training process, to ensure the compliance of the trained model and dataset to the best of our ability. Due to the complexity of the data and the diversity of language model usage scenarios, we cannot guarantee that the dataset is completely free of copyright issues or improper content. If you believe anything infringes on your rights or contains improper content, please contact us, and we will promptly address the matter.
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task_categories:
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- text-to-speech
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library_name: datasets
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license: apache-2.0
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language:
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- zh
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tags:
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- speech
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- emotional-speech
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- voice-cloning
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- mandarin
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dataset_info:
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features:
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- name: audio
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dtype: audio
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- name: text
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dtype: string
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- name: emotion
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dtype: string
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- name: speaker
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dtype: string
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splits:
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- name: train
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num_bytes: 3610108297.64
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num_examples: 4160
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download_size: 3077432286
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dataset_size: 3610108297.64
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configs:
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- config_name: default
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data_files:
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- split: train
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path: data/train-*
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---
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# CSEMOTIONS: High-Quality Mandarin Emotional Speech Dataset
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[Paper](https://huggingface.co/papers/2508.02038) | [Code](https://github.com/AIDC-AI/Marco-Voice)
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[](LICENSE)
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**CSEMOTIONS** is a high-quality Mandarin emotional speech dataset designed for expressive speech synthesis, emotion recognition, and voice cloning research. The dataset contains studio-quality recordings from six professional voice actors across seven carefully curated emotional categories, supporting research in controllable and natural language speech generation.
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- **Name:** CSEMOTIONS
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- **Total Duration:** ~10 hours
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- **Speakers:** 6 (3 male, 3 female) native Mandarin speakers, all professional voice actors
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- **Emotions:** Neutral, Happy, Angry, Sad, Surprise, Disgust, Fear
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- **Language:** Mandarin Chinese
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- **Sampling Rate:** 48kHz, 24-bit PCM
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We used compliance checking algorithms during the training process, to ensure the compliance of the trained model and dataset to the best of our ability. Due to the complexity of the data and the diversity of language model usage scenarios, we cannot guarantee that the dataset is completely free of copyright issues or improper content. If you believe anything infringes on your rights or contains improper content, please contact us, and we will promptly address the matter.
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