MultiEmotionalTTS-Eval (B-CES)

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1. Dataset Summary (English)

The Bilingual Complex Emotional Speech (B-CES) dataset is specifically designed to evaluate TTS models' performance in handling complex emotional transitions and bilingual alignment.

Each audio sample is carefully curated to feature significant emotional fluctuations or shifts within a single sentence. In addition to full-sentence audio, we provide segmented annotations based on specific emotional transition points.

2. Data Fields

The dataset is indexed via .jsonl files and includes the following key fields:

• id: Unique identifier (used for strict 1:1 mapping between English and Chinese subsets).
• original_emotion_pair: The pair of emotions contained within the sentence (e.g., happiness, sadness).
• text: The transcript of the speech.
• audio: Path to the full-sentence audio (supports online preview on Hugging Face).
• split_results: A list of segmented fragments, each containing specific text and its corresponding emotion.
• split_audio_prefix: The path prefix for the segmented audio clips.

3. Emotion Tags

The dataset covers 7 core emotion labels:

• neutral
• happiness
• sadness
• anger
• fear
• disgust
• surprise

4. Usage

You can load the dataset via the datasets library in Python:

from datasets import load_dataset

# Load Chinese subset
dataset_cn = load_dataset("kunge123/MultiEmotionalTTS-Eval", data_files="metadata_cn.jsonl")

# Load English subset
dataset_en = load_dataset("kunge123/MultiEmotionalTTS-Eval", data_files="metadata_en.jsonl")