Initial commit

.gitattributes

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+*.7z filter=lfs diff=lfs merge=lfs -text
+*.arrow filter=lfs diff=lfs merge=lfs -text
+*.bin filter=lfs diff=lfs merge=lfs -text
+*.bz2 filter=lfs diff=lfs merge=lfs -text
+*.ckpt filter=lfs diff=lfs merge=lfs -text
+*.ftz filter=lfs diff=lfs merge=lfs -text
+*.gz filter=lfs diff=lfs merge=lfs -text
+*.h5 filter=lfs diff=lfs merge=lfs -text
+*.joblib filter=lfs diff=lfs merge=lfs -text
+*.lfs.* filter=lfs diff=lfs merge=lfs -text
+*.lz4 filter=lfs diff=lfs merge=lfs -text
+*.mlmodel filter=lfs diff=lfs merge=lfs -text
+*.model filter=lfs diff=lfs merge=lfs -text
+*.msgpack filter=lfs diff=lfs merge=lfs -text
+*.npy filter=lfs diff=lfs merge=lfs -text
+*.npz filter=lfs diff=lfs merge=lfs -text
+*.onnx filter=lfs diff=lfs merge=lfs -text
+*.ot filter=lfs diff=lfs merge=lfs -text
+*.parquet filter=lfs diff=lfs merge=lfs -text
+*.pb filter=lfs diff=lfs merge=lfs -text
+*.pickle filter=lfs diff=lfs merge=lfs -text
+*.pkl filter=lfs diff=lfs merge=lfs -text
+*.pt filter=lfs diff=lfs merge=lfs -text
+*.pth filter=lfs diff=lfs merge=lfs -text
+*.rar filter=lfs diff=lfs merge=lfs -text
+*.safetensors filter=lfs diff=lfs merge=lfs -text
+saved_model/**/* filter=lfs diff=lfs merge=lfs -text
+*.tar.* filter=lfs diff=lfs merge=lfs -text
+*.tar filter=lfs diff=lfs merge=lfs -text
+*.tflite filter=lfs diff=lfs merge=lfs -text
+*.tgz filter=lfs diff=lfs merge=lfs -text
+*.wasm filter=lfs diff=lfs merge=lfs -text
+*.xz filter=lfs diff=lfs merge=lfs -text
+*.zip filter=lfs diff=lfs merge=lfs -text
+*.zst filter=lfs diff=lfs merge=lfs -text
+*tfevents* filter=lfs diff=lfs merge=lfs -text
+# Audio files - uncompressed
+*.pcm filter=lfs diff=lfs merge=lfs -text
+*.sam filter=lfs diff=lfs merge=lfs -text
+*.raw filter=lfs diff=lfs merge=lfs -text
+# Audio files - compressed
+*.aac filter=lfs diff=lfs merge=lfs -text
+*.flac filter=lfs diff=lfs merge=lfs -text
+*.mp3 filter=lfs diff=lfs merge=lfs -text
+*.ogg filter=lfs diff=lfs merge=lfs -text
+*.wav filter=lfs diff=lfs merge=lfs -text
+*.opus filter=lfs diff=lfs merge=lfs -text
+*.webm filter=lfs diff=lfs merge=lfs -text
+# Image files - uncompressed
+*.bmp filter=lfs diff=lfs merge=lfs -text
+*.gif filter=lfs diff=lfs merge=lfs -text
+*.png filter=lfs diff=lfs merge=lfs -text
+*.tiff filter=lfs diff=lfs merge=lfs -text
+# Image files - compressed
+*.jpg filter=lfs diff=lfs merge=lfs -text
+*.jpeg filter=lfs diff=lfs merge=lfs -text
+*.webp filter=lfs diff=lfs merge=lfs -text

.gitignore

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+.venv*
+.aider*
+*.ipynb
+*.html
+.DS_Store

README.md

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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: saamgwokjinji
+    path: data/saamgwokjinji-*
+  - split: seoiwuzyun
+    path: data/seoiwuzyun-*
+  - split: mouzaakdung
+    path: data/mouzaakdung-*
+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: saamgwokjinji
+    num_bytes: 2398591354.589
+    num_examples: 39173
+  - name: seoiwuzyun
+    num_bytes: 1629539808.0
+    num_examples: 24744
+  - name: mouzaakdung
+    num_bytes: 257168872.246
+    num_examples: 4742
+  download_size: 4304923024
+  dataset_size: 4285300034.835
+---
+
+# 張悦楷講《三國演義》《水滸傳》語音數據集
+
+[English](#the-zoeng-jyut-gaai-story-telling-speech-dataset)
+
+## Dataset Description
+
+- **Homepage:** [張悦楷講古語音數據集 The Zoeng Jyut Gaai Story-telling Speech Dataset](https://canclid.github.io/zoengjyutgaai/)
+- **License:** [CC0 1.0 Universal](https://creativecommons.org/publicdomain/zero/1.0/)
+- **Language:** Cantonese
+- **Total Duration:** 112.54 hours
+- **Average Clip Duration:** 5.901 seconds
+- **Median Clip Duration:** 5.443 seconds
+- **Total number of characters:** 1679097
+- **Average characters per clip:** 24.36
+- **Median characters per clip:** 23
+- **Average speech speed:** 4.14 characters per second
+- **Voice Actor:** [張悦楷](https://zh.wikipedia.org/wiki/%E5%BC%A0%E6%82%A6%E6%A5%B7)
+
+呢個係張悦楷講《三國演義》、《水滸傳》、《走進毛澤東的最後歲月》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。本數據集收集嘅係佢最知名嘅三部作品。
+
+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`/source`，為方便直接用作訓練數據，切分後嘅音頻都放喺 `opus/`
+- 所有 opus 音頻皆為 48000 Hz 採樣率。
+- 所有源字幕 SRT 文件都存放喺 `srt/` 路經下，搭配 `source/` 下嘅音源可以直接作為帶字幕嘅錄音直接欣賞。
+- `cut.py` 係切分腳本，將對應嘅音源根據 srt 切分成短句並生成一個文本轉寫 csv。
+- `stats.py` 係統計腳本，運行佢就會顯示成個數據集嘅各項統計數據。
+
+## 下載使用
+
+要下載使用呢個數據集，可以喺 Python 入面直接跑：
+
+```python
+from datasets import load_dataset
+
+ds = load_dataset("CanCLID/zoengjyutgaai")
+```
+
+如果想單純將 `opus/` 入面所有嘢下載落嚟，可以跑下面嘅 Python 代碼，注意要安裝 `pip install --upgrade huggingface_hub` 先：
+
+```python
+from huggingface_hub import snapshot_download
+
+# 如果淨係想下載啲字幕或者源音頻，就將 `opus/*` 改成 `srt/*` 或者 `source/*`
+# If you only want to download subtitles or source audio, change `opus/*` to `srt/*` or `source/*`
+snapshot_download(repo_id="CanCLID/zoengjyutgaai",allow_patterns="opus/*",local_dir="./",repo_type="dataset")
+```
+
+如果唔想用 python，你亦都可以用命令行叫 git 針對克隆個`opus/`或者其他路經，避免將成個 repo 都克隆落嚟浪費空間同下載時間：
+
+```bash
+mkdir zoengjyutgaai
+cd zoengjyutgaai
+git init
+
+git remote add origin https://huggingface.co/datasets/CanCLID/zoengjyutgaai
+git sparse-checkout init --cone
+
+# 指定凈係下載個別路徑
+git sparse-checkout set opus
+
+# 開始下載
+git pull origin main
+```
+
+### 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 `.opus` 格式。
+1. 運行`cut.py`，將每一集 `.opus` 按照 `.srt` 入面嘅時間點切分成一句一個 `.opus`，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, DatasetDict
+from huggingface_hub import login
+
+sg = load_dataset('audiofolder', data_dir='./opus/saamgwokjinji')
+sw = load_dataset('audiofolder', data_dir='./opus/seoiwuzyun')
+mzd = load_dataset('audiofolder', data_dir='./opus/mouzaakdung')
+dataset = DatasetDict({
+    "saamgwokjinji": sg["train"],
+    "seoiwuzyun": sw["train"],
+    "mouzaakdung": mzd["train"],
+})
+
+# 檢查下讀入嘅數據有冇問題
+dataset['mouzaakdung'][0]
+# 準備好個 token 嚟登入
+login()
+# 推上 HuggingFace datasets
+dataset.push_to_hub("CanCLID/zoengjyutgaai")
+```
+
+### 音頻格式轉換
+
+首先要安裝 [ffmpeg](https://www.ffmpeg.org/download.html)，然後運行：
+
+```bash
+# 將下載嘅音源由 webm 轉成 opus
+ffmpeg -i webm/saamgwokjinji/001.webm -c:a copy source/saamgwokjinji/001.opus
+# 或者轉 mp3
+ffmpeg -i mp3/mouzaakdung/001.mp3 -c:a libopus -map_metadata -1 -b:a 48k -vbr on source/mouzaakdung/001.opus
+# 將 opus 轉成無損 wav
+ffmpeg -i source/saamgwokjinji/001.opus wav/saamgwokjinji/001.wav
+```
+
+如果想將所有 opus 文件全部轉換成 wav，可以直接運行`to_wav.sh`:
+
+```
+chmod +x to_wav.sh
+./to_wav.sh
+```
+
+跟住就會生成一個 `wav/` 路經，入面都係 `opus/` 對應嘅音頻。注意 wav 格式非常掗埞，成個 `opus/` 轉晒後會佔用至少 500GB 儲存空間，所以轉換之前記得確保有足夠空間。如果你想對音頻重採樣，亦都可以修改 `to_wav.sh` 入面嘅命令順便做重採樣。
+
+# The Zoeng Jyut Gaai Story-telling Speech Dataset
+
+This is a speech dataset of Zoeng Jyut Gaai story-telling _Romance of the Three Kingdoms_, _Water Margin_ and _The Final Days of Mao Zedong_. [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 three of his most well-known story-telling pieces.
+
+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 `source/`. For the convenice of training, segmented audios are stored in `opus/`.
+- All opus audio are in 48000 Hz sampling rate.
+- All source subtitle SRT files are stored in `srt/`. Use them with the webm files to enjoy subtitled storytelling pieces.
+- `cut.py` is the script for cutting opus audios into senteneces based on the srt, and generates a csv file for transcriptions.
+- `stats.py` is the script for getting stats of this dataset.
+
+## Usage
+
+To use this dataset, simply run in Python:
+
+```python
+from datasets import load_dataset
+
+ds = load_dataset("CanCLID/zoengjyutgaai")
+```
+
+If you only want to download a certain directory to save time and space from cloning the entire repo, run the Python codes below. Make sure you have `pip install --upgrade huggingface_hub` first：
+
+```python
+from huggingface_hub import snapshot_download
+
+# If you only want to download subtitles or source audio, change `opus/*` to `srt/*` or `source/*`
+snapshot_download(repo_id="CanCLID/zoengjyutgaai",allow_patterns="opus/*",local_dir="./",repo_type="dataset")
+```
+
+If you don't want to run python codes and want to do this via command lines, you can selectively clone only a directory of the repo:
+
+```bash
+mkdir zoengjyutgaai
+cd zoengjyutgaai
+git init
+
+git remote add origin https://huggingface.co/datasets/CanCLID/zoengjyutgaai
+git sparse-checkout init --cone
+
+# Tell git which directory you want
+git sparse-checkout set opus
+
+# Pull the content
+git pull origin main
+```
+
+### Audio format conversion
+
+Install [ffmpeg](https://www.ffmpeg.org/download.html) first, then run：
+
+```bash
+# convert all webm into opus
+ffmpeg -i webm/saamgwokjinji/001.webm -c:a copy source/saamgwokjinji/001.opus
+# or into mp3
+ffmpeg -i mp3/mouzaakdung/001.mp3 -c:a libopus -map_metadata -1 -b:a 48k -vbr on source/mouzaakdung/001.opus
+# convert all opus into loseless wav
+ffmpeg -i source/saamgwokjinji/001.opus wav/saamgwokjinji/001.wav
+```
+
+If you want to convert all opus to wav, run `to_wav.sh`:
+
+```
+chmod +x to_wav.sh
+./to_wav.sh
+```
+
+It will generate a `wav/` path which contains all audios converted from `opus/`. Be aware the wav format is very space-consuming. A full conversion will take up at least 500GB space so make sure you have enough storage. If you want to resample the audio, modify the line within `to_wav.sh` to resample the audio while doing the conversion.

align.py

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+import re
+import audioread
+
+
+def fix_srt_delay(input_file, output_file, delay_start_ms, delay_end_ms, audio_file):
+    """
+    Fixes a progressive delay in an SRT file by linearly adjusting timestamps.
+    Gets video duration from an associated audio file.
+
+    Args:
+        input_file: Path to the input SRT file.
+        output_file: Path to the output SRT file with corrected timestamps.
+        delay_start_ms: Delay at the beginning of the video (in milliseconds).
+        delay_end_ms: Delay at the end of the video (in milliseconds).
+        audio_file: Path to the audio file to get duration from.
+    """
+
+    try:
+        with audioread.audio_open(audio_file) as f:
+            total_duration_ms = int(f.duration * 1000)  # Get duration in milliseconds
+    except audioread.NoBackendError:
+        print("Error: No suitable audio backend found. Please install ffmpeg or another supported library.")
+        return
+    except Exception as e:
+        print(f"Error reading audio file: {e}")
+        return
+
+    with open(input_file, 'r', encoding='utf-8') as infile, open(output_file, 'w', encoding='utf-8') as outfile:
+        for line in infile:
+            if '-->' in line:
+                # Extract start and end timestamps
+                start_time_str, end_time_str = line.strip().split(' --> ')
+                start_time_ms = srt_time_to_milliseconds(start_time_str)
+                end_time_ms = srt_time_to_milliseconds(end_time_str)
+
+                # Calculate the adjusted delay for this subtitle
+                progress = start_time_ms / total_duration_ms
+                current_delay_ms = delay_start_ms + progress * (delay_end_ms - delay_start_ms)
+
+                # Adjust the timestamps
+                adjusted_start_time_ms = start_time_ms - current_delay_ms
+                adjusted_end_time_ms = end_time_ms - current_delay_ms
+
+                # Convert back to SRT time format
+                adjusted_start_time_str = milliseconds_to_srt_time(adjusted_start_time_ms)
+                adjusted_end_time_str = milliseconds_to_srt_time(adjusted_end_time_ms)
+
+                # Write the corrected line to the output file
+                outfile.write(f"{adjusted_start_time_str} --> {adjusted_end_time_str}\n")
+            else:
+                # Write non-timestamp lines as they are
+                outfile.write(line)
+
+
+def srt_time_to_milliseconds(time_str):
+    """Converts an SRT timestamp string to milliseconds."""
+    hours, minutes, seconds_milliseconds = time_str.split(':')
+    seconds, milliseconds = seconds_milliseconds.split(',')
+    total_milliseconds = (int(hours) * 3600 + int(minutes) * 60 + int(seconds)) * 1000 + int(milliseconds)
+    return total_milliseconds
+
+
+def milliseconds_to_srt_time(milliseconds):
+    """Converts milliseconds to an SRT timestamp string."""
+    milliseconds = int(milliseconds)
+    seconds, milliseconds = divmod(milliseconds, 1000)
+    minutes, seconds = divmod(seconds, 60)
+    hours, minutes = divmod(minutes, 60)
+    return f"{hours:02d}:{minutes:02d}:{seconds:02d},{milliseconds:03d}"
+
+
+delay_at_start_ms = 10  # Delay at the beginning (you think it starts from 0)
+delay_at_end_ms = 2200  # Delay at the end in milliseconds
+
+for i in range(81, 93):
+    input_srt_file = f'srt/seoiwuzyun/{i:03d}.srt'  # Your input SRT file
+    output_srt_file = f'{i:03d}.srt'  # Output file name
+    audio_file_path = f'source/seoiwuzyun/{i:03d}.opus'  # Your Opus audio file
+
+    fix_srt_delay(input_srt_file, output_srt_file, delay_at_start_ms, delay_at_end_ms, audio_file_path)
+    print(f"SRT file fixed and saved to {output_srt_file}")

cut.py

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+import csv
+import os
+from typing import Literal
+
+import pysrt
+from pydub import AudioSegment
+
+
+def srt_to_segments_with_metadata(srt_file, episode, audio_file, output_dir, metadata_file, subset: Literal["saamgwokjinji", "seoiwuzyun", "mouzaakdung"]):
+    # Load the SRT file
+    subs = pysrt.open(srt_file)
+
+    # Load the audio file (handling Opus)
+    try:
+        audio = AudioSegment.from_file(audio_file, codec="opus")
+    except Exception as e:
+        print(f"Error loading audio file: {audio_file}")
+        print(f"Error message: {e}")
+        return  # Skip this file and move to the next
+
+    # Ensure the output directory exists
+    os.makedirs(output_dir, exist_ok=True)
+
+    # Prepare the metadata file (appending to a single file)
+    with open(metadata_file, mode='a', newline='', encoding='utf-8') as csvfile:
+        csvwriter = csv.writer(csvfile)
+
+        # Write header row if the file is empty
+        if os.stat(metadata_file).st_size == 0:
+            csvwriter.writerow(['id', 'episode_id', 'file_name', 'audio_duration', 'transcription'])
+
+        if subset == "saamgwokjinji":
+            prefix = "sg"
+        elif subset == "seoiwuzyun":
+            prefix = "sw"
+        elif subset == "mouzaakdung":
+            prefix = "mzd"
+
+        for index, sub in enumerate(subs):
+            # Get start and end times in milliseconds
+            start_time = sub.start.ordinal
+            end_time = sub.end.ordinal
+
+            # Calculate duration in seconds
+            duration = (end_time - start_time) / 1000
+
+            # Extract the audio segment
+            segment = audio[start_time:end_time]
+
+            # Define output filenames (using .opus extension)
+            segment_filename = f"{episode}_{index + 1:03d}.opus"
+            segment_id = f"{prefix}_{episode}_{index + 1:03d}"
+            audio_filename = os.path.join(output_dir, segment_filename)
+
+            # Export the audio segment as Opus
+            try:
+                segment.export(audio_filename, format="opus", codec="libopus")
+            except Exception as e:
+                print(f"Error exporting segment: {audio_filename}")
+                print(f"Error message: {e}")
+                continue  # Skip to the next segment
+
+            # Write to the metadata CSV file
+            csvwriter.writerow(
+                [segment_id, episode, f'{episode}/{segment_filename}', f'{duration:.3f}', sub.text])
+
+    print(f"Segmentation of {audio_file} complete. Files saved to: {output_dir}")
+    print(f"Metadata appended to: {metadata_file}")
+
+
+if __name__ == "__main__":
+    # subset = "saamgwokjinji"
+    # subset = "seoiwuzyun"
+    subset = "mouzaakdung"
+
+    print(f"Processing subset: {subset}")
+    # If append to existing metadata file
+    metadata_file = os.path.join("opus", subset, "metadata.csv")  # Define metadata file path here
+
+    for episode in range(1, 11):
+        # If creating new csv
+        # metadata_file = f"{episode}.csv"
+        episode_str = f'{episode:03d}'  # Format episode as 3-digit string
+
+        srt_file = f'srt/{subset}/{episode_str}.srt'
+        audio_file = f'source/{subset}/{episode_str}.opus'
+        output_dir = f'opus/{subset}/{episode_str}'
+
+        # Only process if the audio file exists
+        if os.path.exists(audio_file):
+            srt_to_segments_with_metadata(srt_file, episode_str, audio_file, output_dir, metadata_file, subset)
+        else:
+            print(f"Audio file not found: {audio_file}. Skipping.")

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