Datasets:
File size: 5,606 Bytes
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---
language:
- yue
license: cc0-1.0
size_categories:
- 10K<n<100K
task_categories:
- automatic-speech-recognition
- text-to-speech
- text-generation
- feature-extraction
- audio-to-audio
- audio-classification
- text-to-audio
pretty_name: c
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
tags:
- cantonese
- audio
- art
dataset_info:
features:
- name: audio
dtype: audio
- name: id
dtype: string
- name: episode_id
dtype: int64
- name: audio_duration
dtype: float64
- name: transcription
dtype: string
splits:
- name: train
num_bytes: 38792803349.64
num_examples: 39190
download_size: 38782029113
dataset_size: 38792803349.64
---
# 張悦楷講《三國演義》語音數據集
[主頁 Home page](https://canclid.github.io/zoengjyutgaai/)
[English](#zoeng-jyut-gaai-story-telling-romance-of-the-three-kingdoms-dataset)
呢個係張悦楷講《三國演義》語音數據集。[張悦楷](https://zh.wikipedia.org/wiki/%E5%BC%A0%E6%82%A6%E6%A5%B7)係廣州最出名嘅講古佬 / 粵語説書藝人。佢從上世紀七十年代開始就喺廣東各個收音電台度講古，佢把聲係好多廣州人嘅共同回憶。本數據集《三國演義》係佢最知名嘅作品一。
數據集用途：
- TTS（語音合成）訓練集
- ASR（語音識別）訓練集或測試集
- 各種語言學、文學研究
- 直接聽嚟欣賞藝術！
TTS 效果演示：https://huggingface.co/spaces/laubonghaudoi/zoengjyutgaai_tts
## 説明
- 所有文本都根據 https://jyutping.org/blog/typo/ 同 https://jyutping.org/blog/particles/ 規範用字。
- 所有文本都使用全角標點，冇半角標點。
- 所有文本都用漢字轉寫，無阿拉伯數字無英文字母
- 所有音頻源都存放喺`/webm`，為方便直接用作訓練數據，切分後嘅音頻都重採樣升 44100Hz 放喺 `wav/`
要使用呢個數據集，可以喺 Python 入面直接跑：
## 使用
```python
from datasets import load_dataset
ds = load_dataset("CanCLID/zoengjyutgaai_saamgwokjinji")
```
如果想單純將所有 wav 文件同對應嘅轉寫複製落嚟，可以跑下面嘅命令行嚟針對克隆個`wav/`路經，避免將成個 repo 都克隆落嚟浪費空間同下載時間：
```bash
git clone --filter=blob:none --sparse https://huggingface.co/datasets/CanCLID/zoengjyutgaai_saamgwokjinji
cd zoengjyutgaai_saamgwokjinji
git sparse-checkout init --cone
git sparse-checkout set wav
git checkout
```
### 數據集構建流程
本數據集嘅收集、構建過程係：
1. 從 YouTube 或者國內評書網站度下載錄音源文件，一般都係每集半個鐘長嘅 `.webm` 或者 `.mp3`。
1. 用加字幕工具幫呢啲錄音加字幕，得到對應嘅 `.srt` 文件。
1. 將啲源錄音用下面嘅命令儘可能無壓縮噉轉換成 `.wav` 格式。
1. 運行`cut.py`，將每一集 `.wav` 按照 `.srt` 入面嘅時間點切分成一句一個 `.wav`，然後對應嘅文本寫入本數據集嘅 `xxx.csv`。
1. 然後打開一個 IPython，逐句跑下面嘅命令，將啲數據推上 HuggingFace。
```python
from datasets import load_dataset
from huggingface_hub import login
dataset = load_dataset('audiofolder', data_dir='./wav')
# 檢查下讀入嘅數據有冇問題
dataset['train'][0]
# 準備好個 token 嚟登入
login()
# 推上 HuggingFace datasets
dataset.push_to_hub("CanCLID/zoengjyutgaai_saamgwokjinji")
```
### 將`.webm`無損轉為`.wav`
首先要安裝 [ffmpeg](https://www.ffmpeg.org/download.html)，然後運行：
```bash
ffmpeg -i "001.webm" -vn -ar 44100 -c:a pcm_s16le "001.wav"
```
如果唔想指定採樣率，儘可能無損轉換，可以將上面嘅`-ar 44100`刪去。**本數據集入面所有 wav 都已經轉為 44100 採樣率**。
# Zoeng Jyut Gaai story-telling _Romance of the Three Kingdoms_ voice dataset
This is a speech dataset of Zoeng Jyut Gaai story-telling _Romance of the Three Kingdoms_. [Zoeng Jyut Gaai](https://zh.wikipedia.org/wiki/%E5%BC%A0%E6%82%A6%E6%A5%B7) is a famous actor, stand-up commedian and story-teller (講古佬) in 20th centry Canton. His voice remains in the memories of thousands of Cantonese people. This dataset is built from one of his most well-known story-telling piece: _Romance of the Three Kingdoms_.
Use case of this dataset:
- TTS (Text-To-Speech) training set
- ASR (Automatic Speech Recognition) training or eval set
- Various linguistics / art analysis
- Just listen and enjoy the art piece!
TTS demo: https://huggingface.co/spaces/laubonghaudoi/zoengjyutgaai_tts
## Introduction
- All transcriptions follow the prescribed orthography detailed in https://jyutping.org/blog/typo/ and https://jyutping.org/blog/particles/
- All transcriptions use full-width punctuations, no half-width punctuations is used.
- All transcriptions are in Chinese characters, no Arabic numbers or Latin letters.
- All source audio are stored in `/webm`. For the convenice of training, segmented audios are resampled into 44.1 kHz and stored in `wav/`.
## Usage
To use this dataset, simply run in Python:
```python
from datasets import load_dataset
ds = load_dataset("CanCLID/zoengjyutgaai_saamgwokjinji")
```
To save space and downloading time and avoid clonin the entire repo, you can selectively clone only the `wav./` directory which contains all the wav files and transcriptions:
```bash
git clone --filter=blob:none --sparse https://huggingface.co/datasets/CanCLID/zoengjyutgaai_saamgwokjinji
cd zoengjyutgaai_saamgwokjinji
git sparse-checkout init --cone
git sparse-checkout set wav
git checkout
``` |