correspond to the physical attribute of audio using our pilot data focusing on pitch height and temporal rate. For each pair of singing and spoken description recording, we first measured the relative effect (3rd column: Relative effect ($p_{re}$)). Then, we manipulated the corresponding feature of the song to result in a relative effect equal to 0.61 (corresponding to 0.4 of Cohen's D) and 0.5 (corresponding to no difference, 0.0 of Cohen's D). Specifically, we shifted down the entire $f_0$ for pitch height and slowed down the playback speed for temporal rate. The 4th and 5th columns show actual scale factors identified at each recording and feature. For example, the first row indicates the $f_0$ of the sung version needed to be shifted 730 cents downward to manipulate the difference in this feature between singing and spoken description to be as small as our proposed SESOI of Cohen's D = .4. Similarly, the sixth row indicates the IOIs of singing needed to be multiplied by 0.472 (i.e., each sung note sped up to be 47.2% as short as the original duration) to make no difference against the spoken description recording, meaning the playback speed of singing should be over 2x faster than the original recording. Although there are only 5 recording pairs and this measurement does not directly provide the justification for using 0.4 of Cohen's D, we can see how the current SESOI threshold corresponds to the physical attribute of audio by comparing the 4th and 5th columns (106 cents for pitch height and factor of 0.091 for temporal rate in average), which to we authors seems reasonable borderlines for listeners to notice the change in audio content. The corresponding audio examples are available in our OSF repository (https://osf.io/mzxc8/files/osfstorage/638491c81daa6b1394759086).

<table><caption>Table S1. Overview of our pilot recordings with key features (pitch height [f0] and temporal rate [1/IOI]) manipulated to demonstrate what real examples of song and speech might sound like if they the differences were non-existent (“equivalence”) or negligible (as small as our chosen SESOI [Smallest Effect Size Of Interest]).</caption><thead><tr><th>Vocalizer</th><th>Feature</th><th>Relative effect (p<sub>re</sub>)</th><th>Manipulation to demonstrate SESOI (p<sub>re</sub> = 0.611)</th><th>Manipulation to demonstrate equivalence (p<sub>re</sub> = 0.5)</th></tr></thead><tbody><tr><td>D. Sadaphal (Marathi)</td><td>f<sub>0</sub></td><td>0.992</td><td>-730 cents (i.e., pitch is transposed down such that sung pitch is more than half an octave lower than the original)</td><td>-860 cents</td></tr><tr><td>Nweke (Yoruba)</td><td>f<sub>0</sub></td><td>0.995</td><td>-930 cents</td><td>-1030 cents</td></tr><tr><td>McBride (English)</td><td>f<sub>0</sub></td><td>0.931</td><td>-650 cents</td><td>-770 cents</td></tr><tr><td>Hadavi (Farsi)</td><td>f<sub>0</sub></td><td>0.978</td><td>-430 cents</td><td>-480 cents</td></tr><tr><td>Ozaki (Japanese)</td><td>f<sub>0</sub></td><td>0.997</td><td>-1300 cents</td><td>-1430 cents</td></tr><tr><td>D. Sadaphal (Marathi)</td><td>IOI</td><td>0.931</td><td>x 0.544 (i.e., playback speed is increased by almost 2x such that the duration of each sung note is only 54.4% as fast as the original)</td><td>x 0.472</td></tr><tr><td>Nweke (Yoruba)</td><td>IOI</td><td>0.831</td><td>x 0.622</td><td>x 0.499</td></tr></tbody></table>
<table><tr><td>McBride (English)</td><td>IOI</td><td>0.836</td><td>x 0.530</td><td>x 0.415</td></tr><tr><td>Hadavi (Farsi)</td><td>IOI</td><td>0.932</td><td>x 0.396</td><td>x 0.324</td></tr><tr><td>Ozaki (Japanese)</td><td>IOI</td><td>0.939</td><td>x 0.393</td><td>x 0.320</td></tr></table>
# Appendix 1 Recording protocol

We study how and why song and speech are similar or different throughout the world, and we need your help! We are recruiting collaborators speaking diverse languages who can record themselves singing one short (minimum 30 second) song excerpt, recitation of the same lyrics, spoken description of the song, and an instrumental version of the song's melody. In addition, we ask collaborators to include a transcribed text that segments your words according to the onset of the sound unit (e.g., syllable, note) that you feel reasonable. **The recording/transcription/segmentation process should take less than 2 hours.** (Later we will ask you to check sound recordings that we produce based on your segmented text, which may take up to 2 more hours.)

Collaborators will be **coauthors** on the resulting publication, and will also be **paid a small honorarium** (pending the results of funding applications). In principle, all audio recordings will be published using a [CC BY-NC 4.0](https://creativecommons.org/licenses/by-nc/4.0/) non-commercial open access license, but exceptions can be discussed on a case-by-case basis (e.g., if this conflicts with taboos or policies regarding indigenous data sovereignty). We seek collaborators aged **18 and over** who are speakers of diverse 1st/heritage languages.

Once you have finished the recordings and created the segmented text files, please:

* email us your text files (but NOT your audio recordings) to [psavage@sfc.keio.ac.jp](mailto:psavage@sfc.keio.ac.jp) and [yozaki@sfc.keio.ac.jp](mailto:yozaki@sfc.keio.ac.jp).

* email your **audio recordings** to [globalsongspeech@gmail.com](mailto:globalsongspeech@gmail.com), where they will be securely monitored and checked by our RA, Tomoko Tanaka, who is not a coauthor on the manuscript. This folder shows an example template of one full set of recordings and text files: [https://drive.google.com/drive/folders/1qbYpv_gxy-gOTBpATA3WwtPHkj14-ISU?usp=sharing](https://drive.google.com/drive/folders/1qbYpv_gxy-gOTBpATA3WwtPHkj14-ISU?usp=sharing)

If you have any questions about the protocol, please email:

- Dr. Patrick Savage (psavage@sfc.keio.ac.jp), Associate Professor, Keio University

- Yuto Ozaki (yozaki@sfc.keio.ac.jp), PhD student, Keio University

## [Recording content]

* Please choose one traditional song to record. This should be a song you know how to sing that is one of the oldest/ most “traditional” (loosely defined)/ most familiar to your cultural background. This might be a song sung to you as a child by your parents/relatives/teachers, learned from old recordings, etc. (we plan to include other genres in future stages). Since there is no universally accepted definition of “song” (which is an issue we hope to address in this study), you are free to interpret “song” however feels appropriate in your language/culture. Please contact us if you would like to discuss any complexities of how to define/choose a “traditional song”.

* Please choose a song that you can record yourself singing for a **minimum of 30 seconds**. However, we encourage you to record yourself for as long as makes sense for your song to enable more in-depth future studies without having to go back and re-record yourself (though we request you keep within a maximum of 5 minutes if possible). Note that it is fine if it takes less than 30 seconds to recite the same lyrics when spoken, but please ensure that your free spoken description also lasts a minimum of 30 seconds.
* Please use your **1st/heritage language for every recording** (except for the instrumental track). **If you speak multiple languages**, please choose one language (and let us know which one ahead of time) and avoid combining multiple languages in singing, recitation and spoken description.

* Please record song, lyric recitation, spoken description and instrumental in the order that you feel natural.

○ **Song**: When you sing, please sing solo without instrumental accompaniment, in a pitch range that is comfortable to you. You do not need to follow the same pitch range sung by others. Feel free to sing while reading lyrics/notation if it is helpful.

○ **Lyric recitation**: When you recite the lyrics, please speak in a way you feel is natural. Feel free to read directly from written lyrics if it is helpful.

○ **Spoken description**: Please describe the song you chose (why you chose it, what you like about it, what the song is about, etc.). However, please avoid quoting the lyrics in your description. Again, aim for **minimum 30 seconds**.

○ **Instrumental version**: Please also record yourself playing the melody of your chosen song(s). We would be delighted for you to play with a traditional instrument in your culture or country. Continuous-pitch instruments (e.g., violin, trombone, erhu) are especially helpful, but fixed-pitch instruments (e.g., piano, marimba, koto) are fine, too. Please do not use electronic instruments (e.g. electric keyboard). Choose whatever pitch/key is comfortable for you to play (this need not be the same pitch/key as the sung version). Please contact us if you want to discuss any complexities involved in trying to play your song's melody on an instrument.

➤ If you do not play a melodic instrument, it is also acceptable to just record the song's rhythm using tapping sounds or other percussive sounds (e.g., drums). In this case, this "instrumental" recording will only be used to analyze rhythmic features. In this case, you can tap the rhythm while singing in your head, but please do not sing out loud.

**[Recording method]**

* Please record in a quiet place with minimal background noise.

* Please record each description/recitation/song/instrumental separately as different files. The file name should be "[Given name]_[Surname]_[Language]_Traditional_[Song title]_[YYYYMMDD of the time you record]_[song|recit|desc|inst].[file format]". For example,

* Yuto_Ozaki_Japanese_Traditional_Sakura_20220207-song.wav

* Yuto_Ozaki_Japanese_Traditional_Sakura_20220207_recit.wav

* Yuto_Ozaki_Japanese_Traditional_Sakura_20220207_desc.wav

* Yuto_Ozaki_Japanese_Traditional_Sakura_20220207_inst.wav

* Please ensure that your mouth (or instrument) is the same distance from your recording device for each recording, and please make all recordings during one session (to avoid differences in recording environment and/or your vocal condition on that day).

* Regarding the recording device, a high-quality microphone would be great, but a smartphone or personal computer built-in microphone is also fine. Preferred formats are: .mp4, .MOV, .wav, with sampling rate: 44.1kHz or higher / bit rate: 16bit or higher for .wav and lossless codecs (e.g. Apple Lossless Audio Codec) and 128kbps or higher for .MOV and .mp4 with lossy compression codecs. If you are an iPhone user and considering using the Voice Memos app, please set the "Audio Quality" configuration to "Lossless".
* Note: although we only require and will only publish audio data for the main study, we have found that default audio quality can be higher when recording video via smartphone than when recording audio. Also, when it comes time to publish the findings with accompanying press releases, we plan to ask for volunteers who want to share videos of their own singing/speaking. So if you want to make your initial recordings using video, it may save time if you decide you want to volunteer video materials later on.

[Segmented texts]

* After the recording of spoken description, lyric recitation or song, please create a Word file or Rich Text Format file per recording that segments your utterance based on the onset of acoustic units (e.g., syllable, note) that you feel natural. It is up to you how you divide song/speech into what kind of sound unit.

* Technically, we would like you to focus on the perceptual center or "P-center" (Morton, Marcus, & Frankish, 1976), which is "the specific moment at which a sound is perceived to occur" (Danielsen et al., 2019).

* Segmentation by the acoustic unit of language (e.g. syllable, mora), by the acoustic unit of music (e.g. note, 節 fushi), and by the P-center are not necessarily the same. For example, one syllable may sometimes be sung across multiple notes (and vice versa).

* Please use a vertical bar ("|") to segment recordings (see examples below).

* Please use romanization when writing and also write it based on the phoneme in your native script if it doesn't use Roman characters. You may use IPA (International Phonetic Alphabet) instead of romanization if you prefer.

* Please start a new line in the segmented text at the position where your utterance has a pause for breathing

* When there are successive sound units that keep the same vowels (e.g. "melisma" in Western music, "kobushi" in Japanese music, etc.) and you feel have separate onsets, then you can segment the text by repeating vowels (e.g. A|men → A|a|a|a|men).

* Please include a written English translation of the text of the spoken description and the sung lyrics.

* Example (Japanese)

* **Singing of Omori Jinku**
    (Segmented texts with romanization)
    Ton|Bi|Da|Ko|Na|Ra|Yo|O|O|O
    I|To|Me|Wo|O|Tsu|Ke|E|Te
    Ta|Gu|Ri|Yo|Se|Ma|Su|Yo|O|O
    I|To|Me|Wo|O|Tsu|Ke|E|Te
    Hi|Za|Mo|To|Ni|I|Yo|O
    Ki|Ta|Ko|Ra|Yoi|Sho|Na

(Original lyrics)

鷲風ならヨ 条目をつけて
(コイコイ)
手繰り寄せますヨ 膝元にヨ
(キタコラヨイショナ)

(English translation of the lyrics)

Tie the bridle of a kite kite (Tonbi-dako), pull it in to your knees.
(Kita-ko-ra Yoi-sho-na)

○ **<u>Lyrics recitation of Omori Jinku</u>**

(Segmented texts with romanization)

Ton|Bi|Da|Ko|Na|Ra|Yo
I|To|Me|Wo|Tsu|Ke|Te
Ta|Gu|Ri|Yo|Se|Ma|Su|Yo
Hi|Za|Mo|To|Ni|I|Yo
Ki|Ta|Ko|Ra|Yoi|Sho|Na

○ **<u>Spoken description of Omori Jinku</u>**

(Segmented texts with romanization)

E-|Wa|Ta|Shi|Ga|E|Ran|Da|No|Ha, |Oo|Mo|Ri|Jin|Ku, |To|Iu, |E-, |Tou|Kyou|No|Min|You|De|Su.
Oo|Mo|Ri|To|Iu|No|Ha|Tou|Kyou|No|Ti|Mei|De,
I|Ma|Wa|Son|Na|O|Mo|Ka|Ge|Ha|Na|In|Desu|Ke|Re|Do|Mo
Ko|No|U|Ta|Ga|U|Ta|Wa|Re|Te|I|Ta|To|Ki|Ha,|Sono,|No|Ri|Ga,|Ni|Hon|De|I|Ti|Ban|To|Re|Ru|Ba
|Sho|To|Iu|Ko|To|De,
Maa|Wa|Ri|To|So|No,|Kai|San|Bu|Tsu|De|Nan|Ka|Yuu|Mei|Na, |Ti|I|Ki|Dat|Ta|Mi|Ta|I|De|Su.
Kyo|Ku|No|Ka|Shi|Mo,
E-, |Sou|Des|Ne, |Ho|Shi|Za|Ka|Na, |To|Ka, |Sou|Iu|Ki-|Wa-|Do|Ga|De|Te|Ki|Ma|Su.

(Original spoken description)

えー、私が選んだのは、大森甚句、という、えー、東京の民謡です。

大森というのは東京の地名で、

今はそんな面影はないんですけれども

この歌が歌われていたときは、その、海苔が、日本で一番取れる場所ということで、
邦割とその、海産物でなんか有名な、地域だったみたいです。

曲の歌詞も、

えー、そうですね、干し魚、とか、そういうキーワードが出てきます。

(English translation of the spoken description)

Ah, the song I chose is entitled Omori-Jinku, ah, a Minyo song from Tokyo. Omori is the name of a place in Tokyo, and it has changed a lot these days, but in those days when this song was sung, the place was known for producing the largest amount of nori (seaweed) in Japan, and it also seemed popular due to seafood. Speaking of the lyrics of the song, ah, yeah, like dried fishes, such keywords appear.

• Example (English)

○ **<u>Singing of Scarborough Fair</u>**

(Segmented texts with romanization)

Are |you |go|ing |to |Scar|bo|rough |Fair
Pars|ley, |sage, |rose|ma|ry |and |thyme
Re|mem|ber |me |to |one |who |lives |the|ere
She |once |was |a |true |love |of |mine
Tell |her |to |make |me |a |cam|b|ric |shirt
Pars|ley |sage, |rose|ma|ry |and |thyme
With|out |no |seam |or |nee|dle|wo|ork
Then |she'll |be |a |true |love |of |mine

○ **<u>Lyrics recitation of Scarborough Fair</u>**

(Segmented texts with romanization)
Are |you |go|ing |to |Scar|bo|rough |Fair
Pars|ley, |sage, |rose|ma|ry |and |thyme
Re|mem|ber |me |to |one |who |lives |there
She |once |was |a |true |love |of |mine
Tell |her |to |make |me |a |cam|bric |shirt
Pars|ley |sage, |rose|ma|ry |and |thyme
With|out |no |seams |nor |nee|dle|work
Then |she'll |be |a |true |love |of |mine

## Spoken description of Scarborough Fair

(Segmented texts with romanization)
For |my |tra|di|tio|nal |song |I'm |gon|na |sing |Scar|bo|rough |Fair,|
um, |be|cause |it |is |one |of |the |ol|dest|
songs |that |is, |uh, |quite |well |known |be|cause |it |was, |ah, |made |po|pu|lar |by, |ah, |Paul
|Si|mon |and |Art |Gar|fun|kle.|
Um,
and |it |al|so |has |this |nice |kind |of |haun|ting,|
beau|ti|ful |me|lo|dy |with |this, |uh, |nice |Do|ri|an |scale |that |gives |it |this |kind |of |old
|fa|shioned |feel |that |I |quite |like.|
And |then |the, |the |mea|ning |is |quite |um, |ah, |In|t'res|ting,|
has |this |kind |of |strange,|
um, |im |pos|si|ble |rid|dle |kind |of |theme |where |the,|
ah, |cha|rach|ter |keeps |as|king |the, |um,|
o|thers |to |do |these |im|pos|si|ble |things, |so |it's |kind |of |this|
cryp|tic, |old|fa|shioned |song |that |I, |ah, |I |quite |like.

* Please save the segmented texts of each description/recitation/song separately as different files.
The file name should be "[Given name]_[Surname]_[Language]_Traditional_[Song title]_[YYYYMMDD of the time you record]_[song|recit|desc].[file format]". For example,

* Yuto_Ozaki_Japanese_Traditional_Sakura_20220207-song.docx

* Yuto_Ozaki_Japanese_Traditional_Sakura_20220207_recit.docx

* Yuto Ozaki_Japanese_Traditional_Sakura_20220207_desc.docx

* Therefore, you will upload 7 files in total as your deliverables (i.e. 4 audio files and 3 Word/RTF files) in the end.
Appendix 2 Collaboration agreement form<fnref n="4" />

Collaboration agreement form for "Similarities and differences in a global sample of song and speech recordings"

This project uses an unusual model in which collaborators act as both coauthors and participants. All recorded audio data analyzed will come from coauthors, and conversely all coauthors will provide recorded audio data for analysis. Collaborators will be expected to provide data within 2 months of when these are requested. Please do NOT send data now - we are following a Registered Report model where data must not be collected until the initial research protocol has been peer-reviewed and received In Principle Acceptance. We estimate this will be in early 2023, and ask that you provide your audio recordings and accompanying text within 2 months of In Principle Acceptance. We estimate this recording/annotation will take approximately 1-2 hours to complete. This will be followed by an additional 1-2 hours to check/correct the final files we prepare at a later date.

All collaborators reserve the right to withdraw their coauthorship and data at any time, for any reason, until the manuscript has passed peer review and been accepted for publication. In such cases, their data will be immediately deleted from all computers and servers, public and private (though be aware that if this happens after posting to recognized preprint/data servers such as PsyArXiv or Open Science Framework some data may remain accessible). The corresponding authors (Patrick Savage and Yuto Ozaki) also reserve the right to cancel this collaboration agreement and publish without a given collaborator's data and coauthorhip if necessary (e.g., if data are not provided according to the agreed timeline, or if an insurmountable disagreement about manuscript wording arises). In such a case, any contributions made will be acknowledged in the manuscript.

Collaborators will be coauthors on the resulting publication, and will also be paid a small honorarium (pending the results of funding applications) unless they choose to waive the honorarium. In principle, all audio recordings will be published as supplementary data with this manuscript and permanently archived via recognized preprint/data servers (e.g., PsyArXiv, Open Science Framework, Zenodo) using a CC BY-NC 4.0 non-commercial open access license, but exceptions can be discussed on a case-by-case basis (e.g., if this conflicts with taboos or policies regarding indigenous data sovereignty). We seek collaborators aged 18 and over who speak a diverse range of 1st/heritage languages.

For analysis, we plan to collect and publish demographic information about each collaborator along with their recordings (language name, city language was learned, biological sex [optional], birth year

We thus had to ask collaborators to record themselves several months earlier than they had originally agreed. Most of them managed to do this, but some did not. Because the number of collaborators who could not meet the revised timeline was small enough not to affect our planned power analyses or robustness analyses, we shared the manuscript with all authors and will incorporate those who had not yet made their recordings in the robustness analyses, along with the other authors who made their recordings after knowing the hypotheses.

<footnote n="4">⁴ NB: This agreement had a different timeline from that eventually adopted, because after beginning the process of scheduled review and discussing the issue of confirmation bias with our editor, we concluded that we needed to modify our planned level of bias control from Level 6 ("No part of the data that will be used to answer the research question yet exists and no part will be generated until after IPA [In Principle Acceptance] (so-called 'primary RR')") to Level 2 ("At least some data/evidence that will be used to answer the research question has been accessed and partially observed by the authors, but the authors certify that they have not yet sufficiently observed the key variables within the data to be able to answer the research question AND they have taken additional steps to maximise bias control and rigour (e.g., conservative statistical threshold, recruitment of a blinded analyst, robustness testing, the use of a broad multiverse/specification analysis, or other approaches for controlling risk of bias)"; cf. "Registered Reports with existing data").</footnote>
[optional]). Providing your biological sex or birth year are optional - if you opt not to include these, we will simply exclude your audio data from exploratory analyses that use these variables. (Though please note that biological sex and age may be guessed from your recordings even if you opt not to answer these questions.)

For compliance purposes, CompMusic Lab ("we" or "us") is the data controller of demographic data and audio recordings we hold about you, and you have a right to request information about that data from us (including to access and verify that data). We would like your informed consent to hold and publish demographic data and recordings that you provide to us. All such data will be treated by us under agreed license terms. Please tick the appropriate boxes if you agree and then sign this form:

☐ I agree for my data (audio recordings, written transcriptions, and demographic information [language, city language learned, and biological sex and birth year if provided]) to be used as part of research.

☐ I agree to provide my audio recordings and text annotations within 2 months of the Stage 1 protocol's In Principle Acceptance, and to check/correct the final annotated files within 2 months of their preparation.

☐ I agree to publish my data under a [CC BY-NC 4.0](https://creativecommons.org/licenses/by-nc/4.0/) non-commercial open access license.

a. (If you do not agree to publish your data under CC BY-NC 4.0 [e.g., for reasons relating to Indigenous data sovereignty]) please state your conditions for sharing your audio recording data.:

☐ I agree to be a coauthor of the manuscript.

☐ I agree for a preprint of the manuscript and accompanying data to be posted to recognized preprint/data servers (e.g., PsyArXiv, Open Science Framework, Zenodo).

If you would like to waive the honorarium, you can also tick this box. If you do not waive the honorarium, we will contact you separately to provide bank account details for the wire transfer after you have provided all data.

☐ I choose to waive the honorarium

Name:

Affiliation (e.g., Department, University, Country):

1st/heritage language(s) spoken:

Primary city/town/village(s) where language(s) were learned:

[Optional] Biological sex (e.g., male, female, non-binary, etc.):

[Optional] Birth year:

**Appendix 3: Open call for collaboration to the International Council for Traditional Music (ICTM) email list.** Adapted versions of this email were also used later in tandem with in-person recruitment at the conferences described in the main text). Note that in later meetings we decided to relax the restriction of one collaborator per language, in part due to difficulties of defining the boundaries separating languages and the desire to maximize inclusion.

From: Patrick Savage <psavage@sfc.keio.ac.jp>

Subject: Call for collaboration on global speech-song comparison

Date: July 15, 2022 9:49:57 JST

To: "ictm-l@ictmusic.org" <ictm-l@ictmusic.org>

Dear ICTM-L members,

I am emailing to inquire if any of you are interested in collaborating on a project comparing speech and song in diverse languages around the world to determine what, if any, cross-culturally consistent relationships exist.

I mentioned this project briefly back in January in response to the discussion about Don Niles' post to this list entitled "What is song?". Since then, we have recruited several dozen collaborators speaking diverse languages (see attached rough map), but would like
to open up the call to recruit more. As you can see from the map, our current recruitment is quite unbalanced, particularly lacking speakers of indigenous languages of the Americas, Oceania, and Southeast Asia. We hope you can help us correct that!

<figure><img src="image_24.png" /></figure>

Collaborators will be expected to make short (~30 second) audio recordings of themselves in four ways:

1) singing a traditional song in their native language

2) reciting the lyrics of this song in spoken form

3) describing the meaning of the song in their native language

4) performing an instrumental version of the song's melody on an instrument of their choice (negotiable)

They will also provide written transcriptions of these recordings, segmented into acoustic units (e.g., syllables, notes) and English translations. Later, they will check/correct versions of these recordings created by others with click sounds added to the start of each acoustic unit. Finally, they will help us interpret the results of acoustic comparisons of these recordings/annotations. Our pilot studies suggest that this should all take 2-4 hours for one set of 4 recordings.

Collaborators will be coauthors on the resulting publication, and will also be paid a small honorarium (pending the results of funding applications). In principle, all audio recordings will be published using a CC BY-NC non-commercial open access license, but exceptions can be discussed on a case-by-case basis (e.g., if this conflicts with taboos or policies regarding indigenous data sovereignty).

We seek collaborators aged 18 and over who are native speakers of diverse languages, but we are open to collaborators who are non-native speakers in cases of endangered/threatened languages where there are few native speaker researchers available. During this first stage, we only plan to recruit one collaborator per language, on a first-come first-served basis in principle (in future stages we will recruit multiple speakers per language).

More details and caveats (e.g., how to interpret "traditional" or "song") can be found in a draft protocol here: https://docs.google.com/document/d/1qICFXwew7OEj06dkSoR59TIF7HCmVGcudkenMwHRemM/edit
We actually are not quite ready to begin the formal recording/analysis process yet as we are still working out some methodological and conceptual issues (for which we would also welcome your contributions). The reason I am putting out this call now is that I will be presenting at ICTM in Lisbon next week and I know many of you will also be there, so I wanted to use this chance to reach out in case any of you want to meet and discuss in person in Lisbon.

I'll be mentioning more details about this project briefly during a joint ICTM presentation on "Building Sustainable Global Collaborative Networks" at 9am on July 26th (Session VIA01), and would be delighted to meet anyone interested in collaboration following this session or at any other time during the week of the conference.

Please email me (mentioning your native language[s]) if you're interested in collaborating or in meeting in Lisbon to discuss possibilities!

Cheers,

Pat

---
Dr. Patrick Savage (he/him)
Associate Professor
Faculty of Environment and Information Studies
Keio University SFC (Shonan Fujisawa Campus)
http://compmusic.info
# Stage 2 Supplementary Materials

## S8 Break annotation

Break is defined as the end of a continuous sequence of sounds before relatively long pauses. Breaks are used to avoid creating inter-onset intervals that do not include sounds. For vocal recordings, that would typically constitute when the participant would inhale. In the case of instrumental recordings, how to determine break points between instrumental phrases is up to the person who made the recording, but it is expected to indicate pauses during sound production.

## S9 Exploratory analysis figures

<figure><img src="image_25.png" /><figcaption>**Figure S13.** Effect sizes of each feature using the same data as in Figure 5 but with exploratory comparisons with recitation and instrumental recording types.</figcaption></figure>
<table><caption>**Table S2. Nonparametric trend test (Jonckheere-Terpstra test) for the shift of mean values of features across different acoustic forms.** The category is ordered as 1 = instrumental, 2 = song, 3 = lyrics recitation, and 4 = spoken description. Note that the Jonckheere-Terpstra test assumes observations in each category to be independent of the other categories (e.g., between-subjects design), but our data are collected in a within-subjects design. Therefore, the p-values can be somewhat inaccurate in testing the null hypothesis (i.e., $H_0: \theta_1 = \theta_2 = \theta_3 = \theta_4$) if there is a strong correlation within subjects. The p-values were calculated by a Monte Carlo permutation procedure.</caption><thead><tr><td>Feature</td><td>JT statistics</td><td>P-value</td></tr></thead><tbody><tr><td>Pitch height</td><td>6752</td><td>1.2 x 10<sup>-4</sup></td></tr><tr><td>Temporal rate</td><td>27672</td><td>1.2 x 10<sup>-4</sup></td></tr><tr><td>Pitch stability</td><td>3569</td><td>1.2 x 10<sup>-4</sup></td></tr><tr><td>Timbral brightness</td><td>16864</td><td>1.2 x 10<sup>-4</sup></td></tr><tr><td>Pitch interval size</td><td>13340</td><td>0.30</td></tr><tr><td>Pitch declination</td><td>10288</td><td>1.2 x 10<sup>-4</sup></td></tr><tr><td>Phrase length</td><td>10876</td><td>1.2 x 10<sup>-4</sup></td></tr><tr><td>Intensity</td><td>13787</td><td>3.7 x 10<sup>-4</sup></td></tr><tr><td>Timbral noisiness</td><td>22998</td><td>1.2 x 10<sup>-4</sup></td></tr><tr><td>Rhythmic regularity</td><td>23484</td><td>1.2 x 10<sup>-4</sup></td></tr><tr><td>Pitch interval regularity</td><td>20329</td><td>1.2 x 10<sup>-4</sup></td></tr><tr><td>Pulse clarity</td><td>9911</td><td>1.2 x 10<sup>-4</sup></td></tr><tr><td>Pitch range</td><td>13114.5</td><td>0.20</td></tr></tbody></table>
<figure><img src="image_26.png" /><figcaption>**Figure S14.** Alternative visualization of Figure 9 showing mean values of each feature by biological sex and focusing on the features subject to the main confirmatory analysis. Note that the colors of data points indicate language families, which are coded the same as in Figure 3</figcaption></figure>

<figure><img src="image_27.png" /><figcaption>**Figure S15.** Re-running of the analysis on our full data with automated feature extraction. pYIN (Mauch & Dixon, 2014) was used for f0 extraction and de Jong & Wemp's (2009) Praat script was used for onset timing extraction. Break annotation was not automated so pitch declination was not measured.</figcaption></figure>
<figure><img src="image_28.png" /><figcaption>**Figure S16.** Color mapping of Figure 12.</figcaption></figure>
<figure><img src="image_29.png" /></figure>

**Figure S17.** Supplementary information for Fig. 10. Mean values of pitch height of each recording are displayed. *f*₀s were extracted by pYIN (Mauch & Dixon, 2014). The horizontal lines in the violin plots are median.

<figure><img src="image_30.png" /></figure>

**Figure S18.** Supplementary information for Fig. 10. Mean values of pitch stability of each recording are displayed. *f*₀s were extracted by pYIN (Mauch & Dixon, 2014). The horizontal lines in the violin plots are median.
<figure><img src="image_31.png" /><figcaption>**Figure S19.** Supplementary information for Fig. 10. Mean values of timbral brightness of each recording are displayed. $f_0$s were extracted by pYIN (Mauch & Dixon, 2014). The horizontal lines in the violin plots are median.</figcaption></figure>

<figure><img src="image_32.png" /><figcaption>**Figure S20.** Mapping data by nPVIs of song and spoken description by each collaborator and its song-instrumental version, and the density plot of nPVIs of each. The red lines are linear fitting of nPVIs of spoken description and nPVIs of song, and the dotted line is $y = x$ which can be used to grasp if nPVIs of spoken description is larger than that of song and vice versa.</figcaption></figure>
<figure><img src="image_33.png" /><figcaption>**Figure S21.** Difference between onset times annotated by Ozaki (YO) and onset times annotated by Savage (PES) per recording for the 8 codings re-annotated by Savage to assess inter-rater reliability. The horizontal lines in the violin plots indicate the median. Color is coded as the same in Fig. 3.</figcaption></figure>

<figure><img src="image_34.png" /><figcaption>**Figure S22.** Permutation importance of the features in three binary classifiers.</figcaption></figure>
<table><caption>**Table S3.** Average over performance metrics measured by randomly splitting recording sets into training and test sets 1024 times.</caption><thead><tr><th></th><th></th><th>Logistic regression</th><th>SVM</th><th>Naive Bayes</th></tr></thead><tbody><tr><td colspan="2">Accuracy</td><td>95.78%</td><td>93.75%</td><td>92.94%</td></tr><tr><td rowspan="3">Song</td><td>Precision</td><td>96.66</td><td>92.68</td><td>92.81</td></tr><tr><td>Recall</td><td>95.25</td><td>95.70</td><td>93.98</td></tr><tr><td>F1 score</td><td>95.72</td><td>93.92</td><td>93.03</td></tr><tr><td rowspan="3">Spoken description</td><td>Precision</td><td>95.74</td><td>95.89</td><td>94.45</td></tr><tr><td>Recall</td><td>96.31</td><td>91.80</td><td>91.91</td></tr><tr><td>F1 score</td><td>95.80</td><td>93.50</td><td>92.76</td></tr></tbody></table>

<figure><img src="image_35.png" /><figcaption>**Figure S23.** Correlation matrix of the features within song recordings. The data are the mean values of the features, which are plotted in Figure 6.</figcaption></figure>
Correlation matrix of features (Spoken description)

<figure><img src="image_36.png" /><figcaption>**Figure S24.** Correlation matrix of the features within spoken description recordings. The data are the mean values of the features, which are plotted in Figure 6.</figcaption></figure>
Appendix 3 List of songs

<table><thead><tr><td>#</td><td>Name</td><td>Song title (Romanization)</td><td>Language</td><td>Instrument</td></tr></thead><tbody><tr><td>1</td><td>Nori Jacoby</td><td>Laila Laila</td><td>Modern Hebrew [Jerusalem]</td><td>Whistle</td></tr><tr><td>2</td><td>Limor Raviv</td><td>ירושלים של זהב (Yerushalayim ShelZahav)</td><td>Modern Hebrew [Tel Aviv]</td><td>Tapping</td></tr><tr><td>3</td><td>Iyadh El Kahla</td><td>لاموني اللي غاروا مني</td><td>Tunisian Arabic</td><td>Aerophone</td></tr><tr><td>4</td><td>Utae Ehara</td><td>イタサン (Itasan)</td><td>Aynu (Hokkaido Ainu)</td><td>Tapping</td></tr><tr><td>5</td><td>Neddiel Elcie Muñoz Millalonco</td><td>Ñaumen pu llauken</td><td>Tsesungún (Huilliche)</td><td>Clapping</td></tr><tr><td>6</td><td>Nozuko Nguqu</td><td>Ulele</td><td>IsiXhosa (Xhosa)</td><td>Piano</td></tr><tr><td>7</td><td>Mark Lenini Parselelo</td><td>Lala Mtoto Lala</td><td>Kiswahili (Swahili)</td><td>Tapping</td></tr><tr><td>8</td><td>Cristiano Tsope</td><td>Hiya Tlanguela xinwanana xinga pswaliwa namuntla</td><td>Ronga</td><td>Clapping</td></tr><tr><td>9</td><td>Florence Nweke</td><td>Pat omo o</td><td>Yoruba</td><td>Piano</td></tr><tr><td>10</td><td>Adwoa Arhine</td><td>Yeyc Eguafo</td><td>Fante (Akan)</td><td>Clapping</td></tr><tr><td>11</td><td>Jehoshaphat Philip Sarbah</td><td>Daa na se</td><td>Twi (Akan)</td><td>Piano</td></tr><tr><td>12</td><td>Latyr Sy</td><td>Mbeuguel</td><td>Wolof</td><td>Clapping</td></tr><tr><td>13</td><td>I Putu Gede Setiawan</td><td>Putriceningayu</td><td>Balinese</td><td>Suling</td></tr><tr><td>14</td><td>Suzanne Purdy</td><td>Pōkarekare Ana</td><td>Te Reo Māori (Māori) [Auckland]</td><td>Tapping</td></tr><tr><td>15</td><td>Rob Thorne</td><td>Ko Te Pū</td><td>Te Reo Māori (Māori) [Wellington]</td><td>Kōauau rākau</td></tr><tr><td>16</td><td>Nerea Bello Sagarzazu</td><td>Xoxo Beltza</td><td>Euskara (Basque) [Hondarribia]</td><td>Aerophone</td></tr><tr><td>17</td><td>Urise Kuikuro</td><td>Toló</td><td>Língua Kuikuro (Kuikúro-Kalapálo)</td><td>Clapping</td></tr><tr><td>18</td><td>Shantala Hegde</td><td>Moodala Maneya</td><td>Kannada</td><td>Clapping</td></tr><tr><td>19</td><td>Rytis Ambrazevičius</td><td>Sėjau rugelius</td><td>Lithuanian</td><td>Idiophone</td></tr><tr><td>20</td><td>Tadhg Ó Meachair</td><td>Éiníní</td><td>Gaeilge (Irish)</td><td>Piano Accordion</td></tr><tr><td>21</td><td>Niels Chr. Hansen</td><td>I Skovens Dybe Stille Ro</td><td>Danish</td><td>Piano</td></tr><tr><td>22</td><td>Mark van Tongeren</td><td>Hoor De Wind waait</td><td>Dutch [Heemstede]</td><td>Piano</td></tr><tr><td>23</td><td>Kayla Kolff</td><td>Dikkertje Dap</td><td>Dutch [Nairobi]</td><td>Membranophone</td></tr><tr><td>24</td><td>Adam Tierney</td><td>Simple Gifts</td><td>English [Indiana]</td><td>Electric Piano</td></tr><tr><td>25</td><td>Christina Vanden</td><td>Sleep Now Rest Now</td><td>English [Michigan]</td><td>Cello</td></tr></tbody></table>
<table><tr><td></td><td>Bosch der Nederlanden</td><td></td><td></td><td></td></tr><tr><td>26</td><td>Patrick Savage</td><td>Scarborough Fair</td><td>English [Nevada]</td><td>Piano</td></tr><tr><td>27</td><td>John McBride</td><td>Arthur McBride</td><td>English [Newry]</td><td>Flute</td></tr><tr><td>28</td><td>William Tecumseh Fitch</td><td>Rovin' Gambler</td><td>English [Pennsylvania]</td><td>Guitar</td></tr><tr><td>29</td><td>Peter Pfordresher</td><td>America the Beautiful</td><td>English [Washington D.C.]</td><td>Piano</td></tr><tr><td>30</td><td>Yannick Jadoul</td><td>VandaagIs't Sinte Maarten</td><td>Flemish (Dutch)</td><td>Piano</td></tr><tr><td>31</td><td>Felix Haiduk</td><td>Die Gedanken Sind Frei</td><td>German</td><td>Melodica</td></tr><tr><td>32</td><td>Ulvhild Færøvik</td><td>Nordmannen</td><td>Norwegian</td><td>Clapping</td></tr><tr><td>33</td><td>Daniel Fredriksson</td><td>Ho Maja</td><td>Svenska (Swedish)</td><td>Offerdalspipa</td></tr><tr><td>34</td><td>Emmanouil Benetos</td><td>Saranta Palikaria</td><td>Greek</td><td>Clapping</td></tr><tr><td>35</td><td>Dhwani P. Sadaphal</td><td>Saraswatee maateshwaree</td><td>Hindi</td><td>Harmonium</td></tr><tr><td>36</td><td>Parimal M. Sadaphal</td><td>Sukhakartaa</td><td>Marathi</td><td>Sitar</td></tr><tr><td>37</td><td>Meyha Chhatwal</td><td>बाजरे दा सिंटा (Bajre Da Sitta)</td><td>Punjabi (Eastern Panjabi)</td><td>Harmonium</td></tr><tr><td>38</td><td>Ryan Mark David</td><td>Dil Dil Pakistan</td><td>Urdu</td><td>Acoustic guitar</td></tr><tr><td>39</td><td>Shahaboddin Dabaghi Varnosfaderani</td><td>Morgh e Sahar</td><td>Western Farsi [Isfahan]</td><td>Clapping</td></tr><tr><td>40</td><td>Shafagh Hadavi</td><td>Mah Pishanoo</td><td>Western Farsi [Tehran]</td><td>Piano</td></tr><tr><td>41</td><td>Manuel Anglada-Tort</td><td>La Presó de Lleida</td><td>Catalan</td><td>Piano</td></tr><tr><td>42</td><td>Pauline Larrouy-Maestri</td><td>À la claire fontaine</td><td>French</td><td>Piano</td></tr><tr><td>43</td><td>Andrea Ravignani</td><td>Bella Ciao</td><td>Italian</td><td>Saxophone</td></tr><tr><td>44</td><td>Violeta Magalhães</td><td>O milho da nossa terra</td><td>Portuguese [Porto]</td><td>Tapping</td></tr><tr><td>45</td><td>Camila Bruder</td><td>A Canoa Virou</td><td>Portuguese [São Paulo]</td><td>Tambourine</td></tr><tr><td>46</td><td>Marco Antonio Correa Varella</td><td>Suite do Pescador</td><td>Portuguese [São Paulo]</td><td>Nose flute</td></tr><tr><td>47</td><td>Juan Sebastián Gómez-Cañón</td><td>El pescador</td><td>Spanish [Bogotá]</td><td>Guitar</td></tr><tr><td>48</td><td>Martín Rocamora</td><td>Aquello</td><td>Spanish [Montevideo]</td><td>Guitar</td></tr><tr><td>49</td><td>Javier Silva-Zurita</td><td>Un gorro de lana</td><td>Spanish [Santiago]</td><td>Guitar</td></tr><tr><td>50</td><td>Ignacio Soto-Silva</td><td>El Lobo Chilote</td><td>Spanish [Osorno]</td><td>Clapping</td></tr><tr><td>51</td><td>Dilyana Kurdova</td><td>Zarad tebe, mome, mori</td><td>Bulgarian</td><td>Clapping</td></tr><tr><td>52</td><td>Aleksandar Arabadjiev</td><td>Jovano</td><td>Macedonian</td><td>Kaval</td></tr></table>
<table><tr><td>53</td><td>Wojciech Krzyżanowski</td><td>Wlazł Kotek Na Płotek</td><td>Polish</td><td>Guitar</td></tr><tr><td>54</td><td>Polina Proutskova</td><td>Dusha moia pregreshnaia</td><td>Russian</td><td>Violin</td></tr><tr><td>55</td><td>Vanessa Nina Borsan</td><td>En Hribček Bom Kupil</td><td>Slovenian</td><td>Tapping</td></tr><tr><td>56</td><td>Olena Shcherbakova</td><td>Podolyanochka</td><td>Ukrainian</td><td>Piano</td></tr><tr><td>57</td><td>Diana Hereld</td><td>O'WOn O'WIt (unelanvhi uwetsi)</td><td>Cherokee</td><td>Tapping</td></tr><tr><td>58</td><td>Gakuto Chiba</td><td>津軽よされ節 (Tsugaru-yosarebushi)</td><td>Japanese [Hokkaido]</td><td>Tsugaru-shamisen (津軽三味線)</td></tr><tr><td>59</td><td>Shinya Fujii</td><td>デカンショ節 (Dekansho-bushi)</td><td>Japanese [Hyogo]</td><td>Clapping</td></tr><tr><td>60</td><td>Yuto Ozaki</td><td>大森甚句 (Omori-Jinku)</td><td>Japanese [Tokyo]</td><td>Guitar</td></tr><tr><td>61</td><td>Naruse Marin</td><td>朝花節 (Asabana-bushi)</td><td>Northern Amami-Oshima</td><td>Sanshin (三線)</td></tr><tr><td>62</td><td>Teona Lomsadze</td><td>Nana (Lullaby)</td><td>Georgian</td><td>Chonguri</td></tr><tr><td>63</td><td>Sangbuem Choo</td><td>아리랑 (Arirang)</td><td>Korean</td><td>Guitar</td></tr><tr><td>64</td><td>Patricia Opondo</td><td>Ero Okech Nyawana</td><td>Luo (dholuo) (Luo (Kenya and Tanzania))</td><td>Whistle</td></tr><tr><td>65</td><td>Rogerdison Natsitsabui</td><td>Jakara Wata</td><td>Rikbaktsa</td><td>Clapping</td></tr><tr><td>66</td><td>Jakelin Troy</td><td>Gundji gawalgu yuri</td><td>Ngarigu</td><td>Percussion</td></tr><tr><td>67</td><td>Tutushamum Puri Righi</td><td>Petara</td><td>Puri Kwaytikindo (Puri)</td><td>Terara (bamboo flute)</td></tr><tr><td>68</td><td>Su Zar Zar</td><td>Mya Man Giri</td><td>Myanmar (Burmese)</td><td>Saung-gauk</td></tr><tr><td>69</td><td>Psyche Loui</td><td>梁祝 (Butterfly Lovers)</td><td>Cantonese (Yue Chinese)</td><td>Violin</td></tr><tr><td>70</td><td>Minyu Zeng</td><td>五指山歌 (The Song of the Five-Fingers Mountain)</td><td>HainanHua (Min Nan Chinese)</td><td>Idiophone</td></tr><tr><td>71</td><td>Fang Liu</td><td>送别 (Farewell)</td><td>Mandarin Chinese</td><td>Clapping</td></tr><tr><td>72</td><td>Great Lekakul</td><td>ลาวดวงเตือน (Lao Doung Duan)</td><td>Thai</td><td>"Klui"(ขลุย) (a Thai flute)</td></tr><tr><td>73</td><td>Brenda Suyanne Barbosa</td><td>Apykaxu</td><td>Mbyá-Guaraní</td><td>Clapping</td></tr><tr><td>74</td><td>Polina Dessiatnichenko</td><td>Ay Lachin</td><td>North Azerbaijani</td><td>Tar</td></tr><tr><td>75</td><td>Olcay Muslu</td><td>Uzun Ince Bir Yoldayim</td><td>Turkish</td><td>Tapping</td></tr></table>