Phonetics as a means of nationalising art songs: a comparative music-phonetics study based on Zhao Yuanren’s New Poetry Collection

Figures & data

Figure 1. Conceptual model of the present study.

Conceptual Model of the Study. The conceptual model presented in this paper encompasses four primary components: music, language, pitch embellishment, and units. Within this model, the principal focus lies on exploring the interplay between music and language, specifically examining the connections between note-tone relationships and melody-intonation. Additionally, the study places a significant emphasis on pitch embellishment, considering it a pivotal aspect of the research. The primary acoustic parameters under investigation in this study are pitch, intensity, and duration.

Figure 2. Correlation between Mandarin tones and Zhao Yuanren’s musical composition concept.

A correspondence diagram containing the four expressions of Mandarin Chinese tones and Zhao Yuanren's principles of pitch selection for creating Chinese art songs.

Table 1. Basic Information about the songs and poems included in the New Poetry Collection.

		Music			Poetry
	Title	Notater	Curved structure	Genre	Lyricist	Genre	Subject matter^12	Provenance
1	He/他 (1922)	Chao Yuen Ren	Single Form	Solo	Hu Shi	New poem in five lines	Love category	The Tried and True Collection, second edition, p. 7
2	Little poem/小诗 (1922)	Chao Yuen Ren	Single Form	Solo	Hu Shi	New poem in five lines	Love category	The Tried and True Collection, Updated edition, p. 61
3	Across the Indian Ocean/过印度洋 (1922)	Chao Yuen Ren	Single Form	Solo	Zhou Wuruo	New poem	Scenery category	Selected Poems in the Vernacular, edited by Deyin Xu, vol. 1, p. 20
4	Ballad of Selling Cloth/卖布谣 (1922)	Chao Yuen Ren	Single Diatonic	Solo	Liu Dabai	Four-word Rhyme	Realistic category	Selected Poems in the Vernacular, vol. 2, p. 2
5	Weaving/织布 (1925)	Chao Yuen Ren	Single Diatonic	Solo	Liu Bannong	New poem with four words	Intentional category	The Whip Collection, p. 169
6	Listen to the rain/听雨 (1927)	Chao Yuen Ren	Single Form	Solo	Liu Bannong	New poem in seven lines	Love category	The Whip Collection, supra, p. 22
7	Autumn Bell/秋钟 (1922)	Chao Yuen Ren	Single Diatonic	Solo	Chao Yuen Ren	New poem	Scenery category	The Rhythm of New Poetry in the National Sound, p. 25
8	Labour Song/劳动歌 (1922)	Chao Yuen Ren	Reproduced single trilogy form	Chorus/Solo	<Weekly Review>	New poem	Realistic category	Selected Poems in the Vernacular, vol. 2, pp. 8–9
9	Go up the mountain/上山 (1926)	Chao Yuen Ren	Single Trilogy Form	Solo/Chorus	Hu Shi	New poem	Realistic category	New Tide, vol. 2, no. 2
10	Also micro-cloud/也是微云 (1926)	Chao Yuen Ren	Single Form	Solo	Hu Shi	New poem	Love category	Unpublished
11	How can I not think of her?/教我如何不想他 (1926)	Chao Yuen Ren	A Four-Part Through-Composed Form	Solo	Liu Bnanong	New poem	Love category	The Whip Collection, supra, pp. 90–92
12	Drinking Song in the Camellia/茶花女中的饮酒歌 (1926)^13	Chao Yuen Ren	Single Diatonic	Solo	Translated by Liu Bannong	Drama excerpts	Realistic category	Camellias, pp. 37–39, Gaston cantata
13	Vase Flowers/瓶花 (1927)	Chao Yuen Ren	Single Diatonic	Solo/Duet	Fan Chengda & Hu Shi	Seven-syllable verse; New poem	Love category	Modern Review, vol. 2, no. 49, p. 16
14	Sea Rhythm/海韵 (1927)	Chao Yuen Ren	Cantata in the Fifth Segment	Chorus& Solo	Xu Zhimo	Prose New Poem	Intentional category	Morning Post – Literature Lent

Table 2. Application details.

Applications	Release Date	Research Unit & Author	Versions	Release Information (URL)	Function
SONIC VISUALISER	2021	Initiated and developed in the Centre for Digital Music, Queen Mary University of London Currently maintained primarily by Chris Cannam at Particular Programmes Ltd	4.4	https://sonicvisualiser.org/	Visualisation, analysis, and annotation of music recordings
PRAAT	2022	Paul Boersma and David Weenink, University of Amsterdam	6.2.09	https://www.fon.hum.uva.nl/praat/download_win.html	Speech visualisation and analysis software, which is mainly used for the extraction and analysis of speech fundamental frequency and sound intensity in this study
BEE CUT	2021	NetSure Technology Co.	V.1.7.6.12	https://beecut.cn/	Video-Audio conversion and saving
COOL EDIT PRO	2020	Adobe Systems	2.1	https://www.cooledit.org/	Audio recording, noise reduction, and editing
TONY^i	2015	Matthias Mauch, Chris Cannam, Rachel Bittner, George Fazekas, Justin Salamon, Jiajie Dai, Juan Belloand Simon Dixon	5.13.2	https://code.soundsoftware.ac.uk/projects/tony/wiki/Reference	Software for music F0 analysis and extraction
SIBELIUS	2014	Avid Technology Inc.	7.5	https://www.avid.com/zh/sibelius	Music Notation Software
EXCEL	2018	Microsoft Office	2202	https://www.microsoft.com/zh-cn/microsoft-365/excel	Perform data organisation and calculations
SPSS	2018	IBM	24.0	https://www.ibm.com/cn-zh/products/spss-statistics	Data statistics and analysis

Figure 3. Schematic diagram of the research process.

A schematic diagram of the research process, which include Material Collection, Data Extraction, Data collection, Data Analysis, and Conclusion.

Figure 4. Number of adjacent interval steps in Audio10. A bar chart of the count analysis for Audio 10#s’ adjacent interval in the Appendix. Smaller intervals dominate the musical melody.

Table 3. Voice and music information for Audio #10.

	Audio Duration (s)	Number of F0 (0.01s/each)	Maximum (semitones)	Minimum (semitones)	Standard deviation (semitones)
Speech	140.34	11791	31.01	−4.99	9.68
Music	140.34	9658	36.30	−3.59	5.36

Figure 5. Histogram of frequency statistics of adjacent st in the music (A) and speech (B) audio.

A bar chart counting Audio #10 melodic contour intervals. Figure 6 consists of two plots, with music audio on the left A and speech audio on the right B. Both figures show a clear centrality.

Table 4. Voice and music information for Audio #2.

	Audio Duration (s)	Number of base frequencies (0.01s/each)	Maximum (Hz)	Minimum (Hz)	Standard deviation (Hz)
Speech	11.95	653	304.88	93.15	33.81
Music	37.84	5117	293.06	82.21	41.72

Figure 6. Scatter diagram of the voice recitation’s melodic contour in Audio #2.

A scatter plot which shows the scatter as well as the moving average linear analysis plot based on the F0 data from the speech recitation audio, the poetic metre is marked in centre of the figure. The voice recitation’s melodic contour proceeds from high to low.

Figure 7. Scatter diagram of singing pitch’s melodic contour in Audio #2.

A scatter plot which shows the scatter as well as the linear analysis plot based on the F0 data from the singing pitch audio. The figure consists of three parts, the upper figure (A`) shows the data situation for the main section, and the lower figures (a`1, a`2) show the data situation for each of the two phrases of the main section. The singing pitch’s melodic contour proceeds from high to low.

Table 5. #2 Curved structure diagram.

Structural part	A		A`
Pieces of music	a1	a2	a`1	a`2
	6	6	6	7
Phrase	3 + 3	3 + 3	3 + 3	3 + 4
Tonality	d

Figure 8. Final sentence voice F0 line of #1 (declarative intonation).

Pitch curve of a declarative intonation in Song #1. The direction of the music conforms to the laws of Chinese intonation.

Figure 9. Final sentence voice F0 line of #1 (yes-no interrogative intonation).

Pitch curve of a yes-no interrogative intonation in Song #1. The direction of the music conforms to the laws of Chinese intonation.

Figure 10. The score excerpt of Song #1 final phrase.

A score excerpt of Song #1 final phrase with three kinds of annotation: lyric in Chinese, lyric in English. And pinyin and value of citation tones. A clear correlation appears at the red box in the figure.

Figure 11. Comparison of the F0 of Song #4 selection’s singing (A) and voice(B) melody.

An F0 comparison graph of Song #4 selection's singing and voice melody, including the top and bottom parts. The two figures show a clear reverse contrast at the red box. Figure long description: The horizontal coordinate in Figure is time (s) and the vertical coordinate is fundamental frequency (Hz). The A graph shows the F0 curve (green curve) and the version’s spectrogram (orange-green bottom graph); the B graph shows the F0 (black curve) of the voice recorded by A, labelled using pinyin and pentatonic markers.

Figure 12. The score excerpt of Song #13.

A score excerpt of Song #13 final phrase use to illustrate the pitch-tone correlation with three kinds of annotation: lyric in Chinese, lyric in English. And pinyin and value of citation tones.

Figure 13. Melodic F0 curve for the word ‘身影’ appearing twice in Song #14.

Comparison of the F0 curves for the two occurrences of the word ‘身影’ in Song #14, with four kinds of annotation: score excerpt, lyric in Chinese, lyric in English. And pinyin and value of citation tones. The two clips show a clear contrast in the word ‘影’.

Figure 14. Song#14: A selection of the five tones in Mandarin.

A pitch- tone correlation Schematic, including five kinds of tone (level, rising, falling-rising, falling, light tone). The figure circled in red are examples of the correspondence between Mandarin tones and melodies.

Table 6. Melodic characteristics of tone and melody in Song #14.

	Tonal Melody Characteristics	Music Tone Melody Characteristics
Level Tone (55)	• Numerous examples present. ·Soprano start, flat march.	• The tones are all monophonic, and when the two-level tone characters are connected, the melody is also straight or progressive.
Rising Tone (35)	• They occur less frequently and are fewer in juxtaposition. ·Starting from the middle voice and rising to the highest end.	• The first bar of the score has a third up, and the second bar has a second up by an appoggiatura on the first beat.
Falling-Rising Tone (214)	• The most frequently occurring type of tone. It starts semi-low, drops to the lowest, and then rises to the highest.	• A type of tone that has a lot of pitch fluctuation on a single beat time value. The character ‘海(hai^214)’, which appears twice in the score, shows a second degree of descent and a fourth degree of ascent.
Falling Tone (51)	• Mostly as a non-rhyming word. ·The high note starts and drops to the lowest end.	• The corresponding word sounds are mostly short, non-volatile monophthongs, and occur less frequently in parallel. ·The melodic high part of the score is a third ascending from D to F, but the harmonic part below it has a melodic downward slope.
Light Tone (0)	• The least frequent occurrence. ·Lightness of loudness, short duration, susceptible to the influence of the preceding tone, regularity of the appearance of the tone change.	• The melodic time values are mostly below half a beat, mostly 8th and 16th notes. ·None appear in the power beat position in the beat. ·The pitch of the light tone generally appears to be shifted or oriented in line with the pitch of the preceding and following tones.

Figure 15. Song #14: Score excerpt and intensity curve at huayin.

A huayin-Chinese tone correlation Schematic, including the upper and lower parts, with the red lines framing the segments illustrating the existence of the correspondence. Figure 15 long description: The upper part of Figure 15 shows the musical sound intensity curve, and the lower part shows the corresponding spectral example selection. The horizontal coordinate is time (s) and the vertical coordinate is sound intensity (dB) (Audio #13).

Figure 16. Score excerpt from Song #6 at the appoggiatura (left) and Song #9 with huayin and appoggiatura (right).

A huayin/appoggiatura-Chinese tone correlation Schematic, including the upper and lower parts, with the red lines framing the segments illustrating the existence of the correspondence. Figure long description: The upper part of Figure shows the intensity curve, the lower part shows the corresponding spectral example selection, the horizontal coordinate is time (s), and the vertical coordinate is intensity (dB) (audio material Song #6 and Song #9).