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Record W2062026891 · doi:10.1121/1.4806630

Acoustic differences in the speaking and singing voice

2013· article· en· W2062026891 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueThe Journal of the Acoustical Society of America · 2013
Typearticle
Languageen
FieldSocial Sciences
TopicLanguage and cultural evolution
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsSingingLoudnessAcousticsSpeech recognitionQuality (philosophy)PsychologyCommunicationComputer sciencePhysics

Abstract

fetched live from OpenAlex

Speech and song are universal forms of vocal expression that reflect distinct channels of communication. While these two forms of expression share a common means of sound production, differences in the acoustic properties of speech and song have not received significant attention. Here, we present evidence of acoustic differences in the speaking and singing voice. Twenty-four actors were recorded while speaking and singing different statements with five emotions, two emotional intensities, and two repetitions. Acoustic differences of speech and song were reported in several acoustic parameters, including vocal loudness, spectral properties, and vocal quality. Interestingly, emotion was conveyed similarly in many acoustic features across speech and song. These results demonstrate the entwined nature of speech and song, and provide evidence in support of the shared emergence of speech and song as a form of early proto-language. These recordings form part of our new Ryerson Audio-Visual Database of Emotional Speech and Song (RAVDESS) that will be freely released in 2013.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.160
Threshold uncertainty score0.361

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.016
GPT teacher head0.267
Teacher spread0.251 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it