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35 dataset results for Music

MUSAN is a corpus of music, speech and noise. This dataset is suitable for training models for voice activity detection (VAD) and music/speech discrimination. The dataset consists of music from several genres, speech from twelve languages, and a wide assortment of technical and non-technical noises.

172 PAPERS • NO BENCHMARKS YET

MAESTRO

The MAESTRO dataset contains over 200 hours of paired audio and MIDI recordings from ten years of International Piano-e-Competition. The MIDI data includes key strike velocities and sustain/sostenuto/una corda pedal positions. Audio and MIDI files are aligned with ∼3 ms accuracy and sliced to individual musical pieces, which are annotated with composer, title, and year of performance. Uncompressed audio is of CD quality or higher (44.1–48 kHz 16-bit PCM stereo).

89 PAPERS • NO BENCHMARKS YET

MusicNet

MusicNet is a collection of 330 freely-licensed classical music recordings, together with over 1 million annotated labels indicating the precise time of each note in every recording, the instrument that plays each note, and the note's position in the metrical structure of the composition. The labels are acquired from musical scores aligned to recordings by dynamic time warping. The labels are verified by trained musicians; we estimate a labeling error rate of 4%. We offer the MusicNet labels to the machine learning and music communities as a resource for training models and a common benchmark for comparing results.

39 PAPERS • 1 BENCHMARK

MusicCaps

MusicCaps is a dataset composed of 5.5k music-text pairs, with rich text descriptions provided by human experts. For each 10-second music clip, MusicCaps provides:

36 PAPERS • 1 BENCHMARK

JSB Chorales

The JSB chorales are a set of short, four-voice pieces of music well-noted for their stylistic homogeneity. The chorales were originally composed by Johann Sebastian Bach in the 18th century. He wrote them by first taking pre-existing melodies from contemporary Lutheran hymns and then harmonising them to create the parts for the remaining three voices. The version of the dataset used canonically in representation learning contexts consists of 382 such chorales, with a train/validation/test split of 229, 76 and 77 samples respectively.

32 PAPERS • 1 BENCHMARK

MTG-Jamendo

The MTG-Jamendo dataset is an open dataset for music auto-tagging. The dataset contains over 55,000 full audio tracks with 195 tags categories (87 genre tags, 40 instrument tags, and 56 mood/theme tags). It is built using music available at Jamendo under Creative Commons licenses and tags provided by content uploaders. All audio is distributed in 320kbps MP3 format.

28 PAPERS • NO BENCHMARKS YET

Lakh Pianoroll Dataset

The Lakh Pianoroll Dataset (LPD) is a collection of 174,154 multitrack pianorolls derived from the Lakh MIDI Dataset (LMD).

9 PAPERS • NO BENCHMARKS YET

FineDance

Click to add a brief description of the dataset (Markdown and LaTeX enabled).

7 PAPERS • 1 BENCHMARK

SymphonyNet

First large-scale symphony generation dataset.

7 PAPERS • 1 BENCHMARK

ASAP (Aligned Scores and Performances)

ASAP is a dataset of 222 digital musical scores aligned with 1068 performances (more than 92 hours) of Western classical piano music.

4 PAPERS • NO BENCHMARKS YET

ComMU

ComMU has 11,144 MIDI samples that consist of short note sequences created by professional composers with their corresponding 12 metadata. This dataset is designed for a new task, combinatorial music generation which generate diverse and high-quality music only with metadata through auto-regressive language model.

4 PAPERS • NO BENCHMARKS YET

Multi-Label Classification Dataset Repository

For each dataset we provide a short description as well as some characterization metrics. It includes the number of instances (m), number of attributes (d), number of labels (q), cardinality (Card), density (Dens), diversity (Div), average Imbalance Ratio per label (avgIR), ratio of unconditionally dependent label pairs by chi-square test (rDep) and complexity, defined as m × q × d as in [Read 2010]. Cardinality measures the average number of labels associated with each instance, and density is defined as cardinality divided by the number of labels. Diversity represents the percentage of labelsets present in the dataset divided by the number of possible labelsets. The avgIR measures the average degree of imbalance of all labels, the greater avgIR, the greater the imbalance of the dataset. Finally, rDep measures the proportion of pairs of labels that are dependent at 99% confidence. A broader description of all the characterization metrics and the used partition methods are described in

4 PAPERS • NO BENCHMARKS YET

ATEPP

ATEPP (Automatically Transcribed Expressive Piano Performances)

ATEPP is a dataset of expressive piano performances by virtuoso pianists. The dataset contains 11677 performances (~1000 hours) by 49 pianists and covers 1580 movements by 25 composers. All of the MIDI files in the dataset come from the piano transcription of existing audio recordings of piano performances. Scores in MusicXML format are also available for around half of the tracks. The dataset is organized and aligned by compositions and movements for comparative studies.

3 PAPERS • NO BENCHMARKS YET

Giantsteps

Giantsteps is a dataset that includes songs in major and minor scales for all pitch classes, i.e., a 24-way classification task.

3 PAPERS • 1 BENCHMARK

JS Fake Chorales

A MIDI dataset of 500 4-part chorales generated by the KS_Chorus algorithm, annotated with results from hundreds of listening test participants, with 500 further unannotated chorales.

3 PAPERS • NO BENCHMARKS YET

Fingerprint Dataset

Fingerprint Dataset (Neural Audio Fingerprint Dataset)

This dataset includes all music sources, background noises and impulse-reponses (IR) samples and conversation speech that have been used in the work "Neural Audio Fingerprint for High-specific Audio Retrieval based on Contrastive Learning" ICASSP 2021 (https://arxiv.org/abs/2010.11910).

2 PAPERS • NO BENCHMARKS YET

YouTube8M-MusicTextClips

The YouTube8M-MusicTextClips dataset consists of over 4k high-quality human text descriptions of music found in video clips from the YouTube8M dataset.

2 PAPERS • NO BENCHMARKS YET

AVASpeech-SMAD

AVASpeech-SMAD (AVASpeech-SMAD: A Strongly Labelled Speech and Music Activity Detection Dataset with Label Co-Occurrence)

We propose a dataset, AVASpeech-SMAD, to assist speech and music activity detection research. With frame-level music labels, the proposed dataset extends the existing AVASpeech dataset, which originally consists of 45 hours of audio and speech activity labels. To the best of our knowledge, the proposed AVASpeech-SMAD is the first open-source dataset that features strong polyphonic labels for both music and speech. The dataset was manually annotated and verified via an iterative cross-checking process. A simple automatic examination was also implemented to further improve the quality of the labels. Evaluation results from two state-of-the-art SMAD systems are also provided as a benchmark for future reference.

1 PAPER • NO BENCHMARKS YET

ChMusic

ChMusic is a traditional Chinese music dataset for training model and performance evaluation of musical instrument recognition. This dataset cover 11 musical instruments, consisting of Erhu, Pipa, Sanxian, Dizi, Suona, Zhuiqin, Zhongruan, Liuqin, Guzheng, Yangqin and Sheng.

1 PAPER • NO BENCHMARKS YET

ConductorMotion100

We construct a large-scale conducting motion dataset, named ConductorMotion100, by deploying pose estimation on conductor view videos of concert performance recordings collected from online video platforms. The construction of ConductorMotion100 removes the need for expensive motion-capture equipment and makes full use of massive online video resources. As a result, the scale of ConductorMotion100 has reached an unprecedented length of 100 hours.

1 PAPER • NO BENCHMARKS YET

Dizi

Dizi is a dataset of music style of the Northern school and the Southern School. Characteristics include melody and playing techniques of the two different music styles are deconstructed.

1 PAPER • NO BENCHMARKS YET

Emomusic

Emomusic (Emotion in Music Database)

1000 songs has been selected from Free Music Archive (FMA). The excerpts which were annotated are available in the same package song ids 1 to 1000. Some redundancies were identified, which reduced the dataset down to 744 songs. The dataset is split between the development set (619 songs) and the evaluation set (125 songs). The extracted 45 seconds excerpts are all re-encoded to have the same sampling frequency, i.e, 44100Hz.

1 PAPER • 1 BENCHMARK

Haydn Annotation Dataset

The Haydn Annotation Dataset consists of note onset annotations from 24 experiment participants with varying musical experience. The annotation experiments use recordings from the ARME Virtuoso Strings Dataset.

1 PAPER • NO BENCHMARKS YET

IMEMNET

IMEMNET (Image-MusicEmotion-Matching-Net)

The Image-MusicEmotion-Matching-Net (IMEMNet) dataset is a dataset for continuous emotion-based image and music matching. It has over 140K image-music pairs.

1 PAPER • NO BENCHMARKS YET

Jam-ALT

Jam-ALT (JamALT: A Formatting-Aware Lyrics Transcription Benchmark)

JamALT is a revision of the JamendoLyrics dataset (80 songs in 4 languages), adapted for use as an automatic lyrics transcription (ALT) benchmark.

1 PAPER • 5 BENCHMARKS

Lyra Dataset

Lyra Dataset (A Dataset for Greek Traditional and Folk Music)

Lyra is a dataset of 1570 traditional and folk Greek music pieces that includes audio and video (timestamps and links to YouTube videos), along with annotations that describe aspects of particular interest for this dataset, including instrumentation, geographic information and labels of genre and subgenre, among others.

1 PAPER • NO BENCHMARKS YET

Mid-level perceptual musical features

This dataset contains annotations for 5000 music files on the following music properties:

1 PAPER • NO BENCHMARKS YET

MuVi

MuVi (MusicVideos)

A dataset of music videos with continuous valence/arousal ratings as well as emotion tags.

1 PAPER • NO BENCHMARKS YET

MusicBench

The MusicBench dataset is a music audio-text pair dataset that was designed for text-to-music generation purpose and released along with Mustango text-to-music model. MusicBench is based on the MusicCaps dataset, which it expands from 5,521 samples to 52,768 training and 400 test samples!

1 PAPER • 1 BENCHMARK

Nlakh

Nlakh is a dataset for Musical Instrument Retrieval. It is a combination of the NSynth dataset, which provides a large number of instruments, and the Lakh dataset, which provides multi-track MIDI data.

1 PAPER • NO BENCHMARKS YET

SingFake

SingFake (SingFake: Singing Voice Deepfake Detection)

The rise of singing voice synthesis presents critical challenges to artists and industry stakeholders over unauthorized voice usage. Unlike synthesized speech, synthesized singing voices are typically released in songs containing strong background music that may hide synthesis artifacts. Additionally, singing voices present different acoustic and linguistic characteristics from speech utterances. These unique properties make singing voice deepfake detection a relevant but significantly different problem from synthetic speech detection. In this work, we propose the singing voice deepfake detection task. We first present SingFake, the first curated in-the-wild dataset consisting of 28.93 hours of bonafide and 29.40 hours of deepfake song clips in five languages from 40 singers. We provide a train/val/test split where the test sets include various scenarios. We then use SingFake to evaluate four state-of-the-art speech countermeasure systems trained on speech utterances. We find these sys

1 PAPER • NO BENCHMARKS YET

Song Describer Dataset

The Song Describer Dataset (SDD) contains ~1.1k captions for 706 permissively licensed music recordings. It is designed for use in evaluation of models that address music-and-language (M&L) tasks such as music captioning, text-to-music generation and music-language retrieval.

1 PAPER • NO BENCHMARKS YET

Virtuoso Strings

Virtuoso Strings is a dataset for soft onsets detection for string instruments. It consists of over 144 recordings of professional performances of an excerpt from Haydn's string quartet Op. 74 No. 1 Finale, each with corresponding individual instrumental onset annotations.

1 PAPER • NO BENCHMARKS YET

YM2413-MDB

YM2413-MDB is an 80s FM video game music dataset with multi-label emotion annotations. It includes 669 audio and MIDI files of music from Sega and MSX PC games in the 80s using YM2413, a programmable sound generator based on FM. The collected game music is arranged with a subset of 15 monophonic instruments and one drum instrument.

1 PAPER • NO BENCHMARKS YET

jaCappella

jaCappella is a corpus of Japanese a cappella vocal ensembles (jaCappella corpus) for vocal ensemble separation and synthesis. It consists of 35 copyright-cleared vocal ensemble songs and their audio recordings of individual voice parts. These songs were arranged from out-of-copyright Japanese children's songs and have six voice parts (lead vocal, soprano, alto, tenor, bass, and vocal percussion). They are divided into seven subsets, each of which features typical characteristics of a music genre such as jazz and enka.

1 PAPER • 1 BENCHMARK

Datasets

35 dataset results for Music