遇见数据集

AlienKevin/sbs_cantonese

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Hugging Face2023-10-15 更新2024-03-04 收录
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--- license: cc-by-nc-4.0 language: - yue pretty_name: SBS Cantonese Speech Corpus size_categories: - 100K<n<1M --- # SBS Cantonese Speech Corpus This speech corpus contains **435 hours** of [SBS Cantonese](https://www.sbs.com.au/language/chinese/zh-hant/podcast/sbs-cantonese) podcasts from Auguest 2022 to October 2023. There are **2,519 episodes** and each episode is split into segments that are at most 10 seconds long. In total, there are **189,216 segments** in this corpus. Here is a breakdown on the categories of episodes present in this dataset: <style> table th:first-of-type { width: 5%; } table th:nth-of-type(2) { width: 15%; } table th:nth-of-type(3) { width: 50%; } </style> | Category | SBS Channels | Episodes | |-------------------|----------------------|-------| | news | 中文新聞, 新聞簡報 | 622 | | business | 寰宇金融 | 148 | | vaccine | 疫苗快報 | 71 | | gardening | 園藝趣談 | 58 | | tech | 科技世界 | 56 | | health | 健康快樂人 | 53 | | culture | 文化360 | 49 | | english | 學英語 | 41 | | expert | 專家話你知 | 37 | | interview | 我不是名人 | 20 | | career | 澳洲招職 | 18 | | food | 美食速遞 | 18 | | uncategorized | n/a | 1328 | * Uncategorized episodes are mostly news but also contains other categories listed above. ## Dataset Details ### Dataset Description <!-- Provide a longer summary of what this dataset is. --> - **Curated by:** Kevin Li - **Language(s):** Cantonese, English (only in podcasts categorized as "english") - **License:** Creative Commons Attribution Non-Commercial 4.0 ### Scraper <!-- Provide the basic links for the dataset. --> - **Repository:** https://github.com/AlienKevin/sbs_cantonese ## Uses Each episode is split into segments using [silero-vad](https://github.com/snakers4/silero-vad). Since silero-vad is not trained on Cantonese data, the segmentation is not ideal and often break sentences in the middle. Hence, this dataset is not intended to be used for supervised ASR. Instead, it is intended to be used for self-supervised speech pretraining, like training WavLM, HuBERT, and Wav2Vec. ### Format Each segment is stored as a monochannel FLAC file with a sample rate of 16k Hz. You can find the segments under the `audio/` folder, where groups of segments are bundled into a .tar.gz file for ease of distribution. The filename of the segment shows which episodes it belongs to and place of it within that episode: For example, here's a filename: ``` 0061gy0w8_0000_5664_81376 ``` where * `0061gy0w8` is the episode id * `0000` means that it is the first segment of that episode * `5664` is the starting sample of this segment. Remember all episodes are sampled at 16k Hz, so the total number of samples in an episode is (the duration in seconds * 16,000). * `81376` is the ending (exclusive) sample of this segment. ### Metadata Metadata for each episode is stored in the `metadata.jsonl` file, where each line stores the metadata for one episode: Here's the metadata for one of the episodes (split into multiple lines for clarity): ```json { "title": "SBS 中文新聞 (7月5日)", "date": "05/07/2023", "view_more_link": "https://www.sbs.com.au/language/chinese/zh-hant/podcast-episode/chinese-news-5-7-2023/tl6s68rdk", "download_link": "https://sbs-podcast.streamguys1.com/sbs-cantonese/20230705105920-cantonese-0288b7c2-cb6d-4e0e-aec2-2680dd8738e0.mp3?awCollectionId=sbs-cantonese&awGenre=News&awEpisodeId=20230705105920-cantonese-0288b7c2-cb6d-4e0e-aec2-2680dd8738e0" } ``` where * `title` is the title of the episode * `date` is the date when the episode is published * `view_more_link` is a link to the associated article/description for this episode. Many news episodes have extremely detailed manuscripts written in Traditional Chinese while others have briefer summaries or key points available. * `download_link` is the link to download the audio for this episode. It is usually hosted on [streamguys](https://www.streamguys.com/) but some earlier episodes are stored SBS's own server at https://images.sbs.com.au. The id of each episode appears at the end of its `view_more_link`. It appears to be a precomputed hash that is unique to each episode. ```python id = view_more_link.split("/")[-1] ```

license: CC BY-NC 4.0 language: - 粤语 pretty_name: SBS粤语语音语料库 size_categories: - 10万<样本数<100万 --- # SBS粤语语音语料库 本语音语料库包含**435小时**的[SBS粤语广播](https://www.sbs.com.au/language/chinese/zh-hant/podcast/sbs-cantonese)播客内容,采集时间为2022年8月至2023年10月。 本语料库共计**2519集**播客,每集被切割为最长不超过10秒的语音片段,总计**189216个片段**。 本数据集的播客分类详情如下: <style> table th:first-of-type { width: 5%; } table th:nth-of-type(2) { width: 15%; } table th:nth-of-type(3) { width: 50%; } </style> | 类别 | SBS频道 | 集数 | |-------------------|----------------------|-------| | 新闻 | 中文新聞、新聞簡報 | 622 | | 商业 | 寰宇金融 | 148 | | 疫苗 | 疫苗快報 | 71 | | 园艺 | 園藝趣談 | 58 | | 科技 | 科技世界 | 56 | | 健康 | 健康快樂人 | 53 | | 文化 | 文化360 | 49 | | 英语学习 | 學英語 | 41 | | 专家访谈 | 專家話你知 | 37 | | 人物访谈 | 我不是名人 | 20 | | 职场招聘 | 澳洲招職 | 18 | | 美食 | 美食速遞 | 18 | | 未分类 | 无 | 1328 | * 未分类播客大多属于新闻类别,同时也包含上述其他类别的内容。 ## 数据集详情 ### 数据集描述 <!-- Provide a longer summary of what this dataset is. --> - **整理者:** Kevin Li - **语言:** 粤语、英语(仅在“英语学习”类播客中出现) - **许可证:** 知识共享署名-非商业性使用4.0国际协议(CC BY-NC 4.0) ### 爬虫工具 <!-- Provide the basic links for the dataset. --> - **代码仓库:** https://github.com/AlienKevin/sbs_cantonese ## 数据集用途 本数据集采用[silero-vad](https://github.com/snakers4/silero-vad)工具对每集播客进行语音切割。 由于silero-vad未针对粤语数据进行训练,因此切割效果并不理想,时常会将句子中途截断。 因此,本数据集不适用于有监督自动语音识别(Automatic Speech Recognition,ASR)任务,而是适用于自监督语音预训练任务,例如训练WavLM、HuBERT及Wav2Vec模型。 ### 数据格式 每个语音片段以单声道FLAC格式存储,采样率为16kHz。所有片段均存放于`audio/`目录下,为便于分发,片段组被打包为.tar.gz压缩文件。 语音片段的文件名包含其所属播客集及在该集中的位置信息,示例如下: 0061gy0w8_0000_5664_81376 其中: * `0061gy0w8` 为播客集ID * `0000` 表示该片段为该播客集的第一个片段 * `5664` 为本片段的起始采样点。由于所有播客集均以16kHz采样,因此单集的总采样点数 = 时长(秒) × 16000。 * `81376` 为本片段的终止采样点(不包含该点)。 ### 元数据 每集播客的元数据存储于`metadata.jsonl`文件中,文件内每行对应一集播客的元数据: 以下为单集播客的元数据示例(为便于阅读已拆分为多行): json { "title": "SBS 中文新聞 (7月5日)", "date": "05/07/2023", "view_more_link": "https://www.sbs.com.au/language/chinese/zh-hant/podcast-episode/chinese-news-5-7-2023/tl6s68rdk", "download_link": "https://sbs-podcast.streamguys1.com/sbs-cantonese/20230705105920-cantonese-0288b7c2-cb6d-4e0e-aec2-2680dd8738e0.mp3?awCollectionId=sbs-cantonese&awGenre=News&awEpisodeId=20230705105920-cantonese-0288b7c2-cb6d-4e0e-aec2-2680dd8738e0" } 各字段说明如下: * `title`:播客集的标题 * `date`:播客集的发布日期 * `view_more_link`:指向该播客集相关文章或详情页面的链接。多数新闻类播客附带详细的繁体中文文稿,其余播客则提供简要总结或核心要点。 * `download_link`:该播客集音频的下载链接。通常托管于[streamguys](https://www.streamguys.com/)平台,但部分早期播客存储于SBS官方服务器https://images.sbs.com.au。 每集播客的ID位于其`view_more_link`的末尾,该ID为预计算的哈希值,可唯一标识单集播客。 python id = view_more_link.split("/")[-1]

提供机构:
AlienKevin
原始信息汇总

SBS Cantonese Speech Corpus

数据集概述

  • 时长: 435小时
  • 时间段: 2022年8月至2023年10月
  • 来源: SBS Cantonese 播客
  • 集数: 2,519集
  • 分段: 每集分为最多10秒的片段,共189,216个片段

分类统计

分类 SBS频道 集数
新闻 中文新聞, 新聞簡報 622
商业 寰宇金融 148
疫苗 疫苗快報 71
园艺 園藝趣談 58
科技 科技世界 56
健康 健康快樂人 53
文化 文化360 49
英语 學英語 41
专家 專家話你知 37
采访 我不是名人 20
职业 澳洲招職 18
食物 美食速遞 18
未分类 n/a 1328
  • 未分类的集数主要是新闻,但也包含上述其他分类。

数据集详情

数据集描述

  • 策划者: Kevin Li
  • 语言: 粤语,英语(仅在“英语”分类的播客中)
  • 许可证: Creative Commons Attribution Non-Commercial 4.0

使用说明

  • 分段工具: 使用 silero-vad 进行分段,但由于该工具未针对粤语数据进行训练,分段效果不理想,常在句子中间断句。
  • 适用场景: 不建议用于监督式自动语音识别(ASR),更适合用于自监督语音预训练,如训练 WavLM、HuBERT 和 Wav2Vec。

格式

  • 音频格式: 每个分段存储为单声道 FLAC 文件,采样率为 16k Hz。
  • 文件命名: 文件名显示分段所属的集数及在该集中的位置。例如:0061gy0w8_0000_5664_81376,其中 0061gy0w8 是集数ID,0000 表示该集的第一个分段,5664 是该分段的起始采样点,81376 是结束采样点(不包括)。

元数据

  • 元数据文件: metadata.jsonl,每行存储一个集数的元数据。

  • 元数据示例: json { "title": "SBS 中文新聞 (7月5日)", "date": "05/07/2023", "view_more_link": "https://www.sbs.com.au/language/chinese/zh-hant/podcast-episode/chinese-news-5-7-2023/tl6s68rdk", "download_link": "https://sbs-podcast.streamguys1.com/sbs-cantonese/20230705105920-cantonese-0288b7c2-cb6d-4e0e-aec2-2680dd8738e0.mp3?awCollectionId=sbs-cantonese&awGenre=News&awEpisodeId=20230705105920-cantonese-0288b7c2-cb6d-4e0e-aec2-2680dd8738e0" }

    • title:集数标题
    • date:发布日期
    • view_more_link:相关文章/描述链接
    • download_link:音频下载链接
  • 集数ID: 集数ID出现在 view_more_link 的末尾,是一个预计算的哈希值,每个集数唯一。 python id = view_more_link.split("/")[-1]

搜集汇总
数据集介绍
AlienKevin/sbs_cantonese 数据集图片
以上内容由遇见数据集搜集并总结生成
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