Datasets:
TW Daily Dialogue Audio Dataset
TW 日常對話語音資料集
This dataset, tw-daily-dialogue-audio, contains synthetic Mandarin daily-life dialogues generated using CosyVoice, specifically FunAudioLLM/Fun-CosyVoice3-0.5B-2512.
本資料集 tw-daily-dialogue-audio 收錄由 CosyVoice 所生成的中文(日常)合成對話語音資料,實際使用的模型為 FunAudioLLM/Fun-CosyVoice3-0.5B-2512。
The data is organized in a multi-turn dialogue format and is suitable for research and applications such as Text-to-Speech (TTS), spoken dialogue systems, and speech understanding.
資料以多輪對話形式組織,適用於 語音合成(TTS)、語音對話系統 與 語音理解 等研究與應用。
Quality Control / Filtering
品質控管與資料過濾
All samples in this dataset are automatically filtered using ASR, and only utterances with Character Error Rate (CER) < 15% are retained.
本資料集所有樣本皆經由 自動語音辨識(ASR)進行過濾,僅保留 字元錯誤率(CER)小於 15% 的語音資料。
The ASR system used for transcription is MediaTek-Research/Breeze-ASR-25.
本資料集所使用的自動語音辨識模型為 MediaTek-Research/Breeze-ASR-25。
The CER is computed between the ground-truth text (text) and the ASR-transcribed text (pred_text) and is intended only as an automatic quality filter, not as human-level validation.
CER 的計算方式為標準文字(text)與 ASR 轉錄結果(pred_text)之間的差異,僅作為自動化品質篩選依據,不代表人工或主觀聽感驗證。
⚠️ This dataset is NOT a human-validated or manually verified TTS dataset.
⚠️ 本資料集並非經過人工驗證或主觀評分的 TTS 資料集。
Acknowledgements
致謝
We would like to thank the following contributors for their support and contributions to this project:
我們誠摯感謝以下貢獻者對本專案的支持與投入:
Timbre Seed: Contributed by Jaron
音色種子(Timbre Seed): 由 Jaron 提供Dataset: Contributed by Liang Hsun
資料集製作(Dataset): 由 Liang Hsun 貢獻This dataset is contributed to Twinkle AI
本資料集貢獻給 Twinkle AI
Schema
資料結構說明
dialogue_id: Identifier of a dialogue session
dialogue_id:對話工作階段的識別碼turn_id: The order of the utterance within a dialogue
turn_id:該句在對話中的順序audio: Synthetic speech audio (24kHz) generated by Fun-CosyVoice3-0.5B-2512
audio:由 Fun-CosyVoice3-0.5B-2512 生成的合成語音(24kHz)text: Ground-truth transcript used for speech generation
text:用於語音生成的標準文字內容pred_text: ASR-transcribed text generated by Breeze-ASR-25
pred_text:由 Breeze-ASR-25 產生的 ASR 轉錄文字cer: Character Error Rate between
textandpred_text
cer:text與pred_text之間的字元錯誤率(CER)
Usage
使用方式
from datasets import load_dataset
ds = load_dataset("OKHand/tw-daily-dialogue2Voice")
# Inspect a sample (grouped by dialogue)
# 查看資料範例(以對話為單位)
print(ds[0])
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