--- license: mit task_categories: - time-series-forecasting language: - en tags: - music - art pretty_name: Song Structure Annotation Database size_categories: - n<1K viewer: false --- # Dataset Card for Song Structure The raw dataset comprises 300 pop songs in .mp3 format, sourced from the NetEase music, accompanied by a structure annotation file for each song in .txt format. The annotator for music structure is a professional musician and teacher from the China Conservatory of Music. For the statistics of the dataset, there are 208 Chinese songs, 87 English songs, three Korean songs and two Japanese songs. The song structures are labeled as follows: intro, re-intro, verse, chorus, pre-chorus, post-chorus, bridge, interlude and ending. Fig. 7 shows the frequency of each segment label that appears in the set. The labels chorus and verse are the two most prevalent segment labels in the dataset and they are the most common segment in Western popular music. Among them, the number of “Postchorus” tags is the least, with only two present. ## Dataset Description - **Homepage:** - **Repository:** - **Paper:** - **Leaderboard:** - **Point of Contact:** ### Dataset Summary Unlike the above three datasets for classification, this one has not undergone pre-processing such as spectrogram transform. Thus we provide the original content only. The integrated version of the dataset is organized based on audio files, with each item structured into three columns: The first column contains the audio of the song in .mp3 format, sampled at 22,050 Hz. The second column consists of lists indicating the time points that mark the boundaries of different song sections, while the third column contains lists corresponding to the labels of the song structures listed in the second column. Strictly speaking, the first column represents the data, while the subsequent two columns represent the label. ### Supported Tasks and Leaderboards time-series-forecasting ### Languages Chinese, English ## Usage ```python from datasets import load_dataset dataset = load_dataset("ccmusic-database/song_structure") for item in ds["train"]: print(item) for item in ds["validation"]: print(item) for item in ds["test"]: print(item) ``` ## Dataset Structure | audio(.wav, 22050Hz) | mel(.jpg, 22050Hz) | label | | :-------------------------------------------------------------------------------------------------------------------------------------: | :-------------------------------------------: | :-----------------------------------------------------: | |