ChatMusician
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Datasets, Benchmark and Models of ChatMusician: Understanding and Generating Music Intrinsically with LLM
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int64 13
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13 | Read the following questions from the four options (A, B, C and D) given in each question. Choose the best option | Use the example below to answer the question that follows.
Which of the following best describes the seventh chord in the above example? | {
"A": "Major seventh in third inversion",
"B": "Dominant seventh in second inversion",
"C": "Major/minor seventh in third inversion",
"D": "Minor seventh in second inversion"
} | knowledge | A | dev | L:1/4
M:4/4
K:D
[FGBd]4 |] %1 | The chord in the given example has G as its root, so that the chord in root position can be spelled: G-B-D-F#. Because the interval from G to F# is a major seventh, rather than a minor 7th, the chord is a major 7th chord. The 7th note of the chord—F#—is in the bass, which indicates that the chord is in third inversion, thus the correct answer is A: major seventh in third inversion. |
41 | Read the following questions from the four options (A, B, C and D) given in each question. Choose the best option | Use the example below to answer the question that follows.
Which of the following is the name of the note in the above example? | {
"A": "C-sharp",
"B": "E-sharp",
"C": "A-sharp",
"D": "G-sharp"
} | knowledge | C | dev | L:1/4
M:4/4
K:E
^a4 |] %1 | In the treble clef, the lines from bottom to top are: E, G, B, D, F. From the fifth line on the treble clef, the first ledger line above that is an interval of one-third higher. Because the top line is F, an interval of a third up would be A. The correct answer then, is A#, answer choice C. |
47 | Read the following questions from the four options (A, B, C and D) given in each question. Choose the best option | Use the example below to answer the question that follows.
Which of the following is the name of the note in the above example? | {
"A": "B-flat",
"B": "D",
"C": "B",
"D": "D-flat"
} | knowledge | D | dev | L:1/4
M:4/4
K:Cb
D,4 |] %1 | The note in the example is D-flat. The key signature contains seven flats: Bb, Eb, Ab, Db, Gb, Cb, and Fb; therefore, the answer can be neither B nor C. The third line of the bass clef is always D for a correct answer of D-flat; a careless error may result in reading the third line as B which is only valid in the treble clef. |
88 | Read the following questions from the four options (A, B, C and D) given in each question. Choose the best option | Use the example below to answer the question that follows.Which of the following chord progressions best describes the above example? | {
"A": "ii\n6\n/\n4 – V – vi\n6 - iii\n",
"B": "I\n6 – IV – V6\n/\n4 - ii",
"C": "IV – V6\n/\n4 – I - ii\n",
"D": "iii\n6 – V – I\n6\n/\n4 - IV"
} | knowledge | B | dev | L:1/4
M:4/4
K:E
[G,B,E] [A,CE] [F,B,D] [F,A,C] |] %1 | The chords in the example are: E major in first inversion, A major in root position, B major in second inversion, and F# minor in root position. In the key of E major, the chords given should be written in Roman numerals relative to their scale degrees in the key (E-F#- |
100 | Read the following questions from the four options (A, B, C and D) given in each question. Choose the best option | Use the example below to answer the question that follows.
The chord in the above example can be best described as which of the following? | {
"A": "viio",
"B": "V",
"C": "ii",
"D": "iv"
} | knowledge | A | dev | L:1/4
M:4/4
K:F#
[EGB]4 |] %1 | The chord in the given example is an E# fully diminished triad. In the key of F# major, this chord is built on the seventh scale degree of F# major scale (F#-G#-A#-B-C#-D#-E#-F#). In standard music theory notation, the E# fully diminished chord can be written in Roman numerals as viio, answer A. |
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Dataset Card for MusicTheoryBench
MusicTheoryBench is a benchmark designed to assess the advanced music understanding capabilities of current LLMs.
You can easily load it:
from datasets import load_dataset
dataset = load_dataset("m-a-p/MusicTheoryBench")
The evaluation code will be available in the coming weeks.
Dataset Structure
MusicTheoryBench consists of 372 questions, formatted as multiple-choice questions, each with 4 options, among which only one is correct. There are 269 questions on music knowledge and 98 questions on music reasoning, along with 5 questions held out for enabling few-shot evaluation.
Dataset Details
Despite the significant advancements in music information retrieval,the definition of advanced music understanding capabilities remains unclear in current research. To measure the advanced understanding abilities of existing LLMs in music, MAP first define two critical elements of music understanding: music knowledge and music reasoning. Definition of music knowledge and reasoning is discussed in ChatMusician paper.
music knowledge subset
In the music knowledge subset, the questions span Eastern and Western musical aspects. It includes 30 topics such as notes, rhythm, beats, chords, counterpoint, orchestration and instrumentation, music-related culture, history, etc. Each major area undergoes targeted examination under the guidance of experts and is divided into various subcategories. For example, in the triads section, the test set specifically examines the definition, types, and related technical details of triads. This test also features different levels of difficulty, corresponding to the high school and college levels of music major students.
music reasoning subset
Most of the questions in the reasoning subset require both music knowledge and reasoning capabilities. Correctly answering these questions requires detailed analysis of the given information and multi-step logical reasoning, calculating chords, melodies, scales, rhythms, etc.
Curation Process
To ensure consistency with human testing standards, MusicTheoryBenchmark is crafted by a professional college music teacher according to college-level textbooks and exam papers. The content underwent multiple rounds of discussions and reviews by a team of musicians. The team carefully selected questions and manually compiled them into JSON and ABC notation. The questions are then labeled into music knowledge and music reasoning subsets. Since the teacher is from China, half of the questions are delivered in Chinese, and later translated into English with GPT-4 Azure API and proofread by the team.
Languages
MusicTheoryBench primarily contains English.
Limitations
- The MusicThoeryBench results reported in ChatMusician paper are obtained with perplexity mode. Direct generation may result in a worse performance. See Opencompass documentaion for more details.
Citation
If you find our work helpful, feel free to give us a cite.
@misc{yuan2024chatmusician,
title={ChatMusician: Understanding and Generating Music Intrinsically with LLM},
author={Ruibin Yuan and Hanfeng Lin and Yi Wang and Zeyue Tian and Shangda Wu and Tianhao Shen and Ge Zhang and Yuhang Wu and Cong Liu and Ziya Zhou and Ziyang Ma and Liumeng Xue and Ziyu Wang and Qin Liu and Tianyu Zheng and Yizhi Li and Yinghao Ma and Yiming Liang and Xiaowei Chi and Ruibo Liu and Zili Wang and Pengfei Li and Jingcheng Wu and Chenghua Lin and Qifeng Liu and Tao Jiang and Wenhao Huang and Wenhu Chen and Emmanouil Benetos and Jie Fu and Gus Xia and Roger Dannenberg and Wei Xue and Shiyin Kang and Yike Guo},
year={2024},
eprint={2402.16153},
archivePrefix={arXiv},
primaryClass={cs.SD}
}
Dataset Card Contact
Authors of ChatMusician.
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