Bruder Camila, Larrouy-Maestri Pauline
Max Planck Institute for Empirical Aesthetics, Grüneburgweg 14, 60322, Frankfurt Am Main, Germany.
Center for Language, Music, and Emotion (CLaME), New York, NY, USA.
Behav Res Methods. 2025 Apr 11;57(5):142. doi: 10.3758/s13428-025-02664-9.
The human voice is remarkably versatile and can vary greatly in sound depending on how it is used. An increasing number of studies have addressed the differences and similarities between the singing and the speaking voice. However, finding adequate stimuli material that is at the same time controlled and ecologically valid is challenging, and most datasets lack variability in terms of vocal styles performed by the same voice. Here, we describe a curated stimulus set of vocalizations where 22 female singers performed the same melody excerpts in three contrasting singing styles (as a lullaby, as a pop song, and as an opera aria) and spoke the text aloud in two speaking styles (as if speaking to an adult or to an infant). All productions were made with the songs' original lyrics, in Brazilian Portuguese, and with a/lu/sound. This ecologically valid dataset of 1320 vocalizations was validated through a forced-choice lab experiment (N = 25 for each stimulus) where lay listeners could recognize the intended vocalization style with high accuracy (proportion of correct recognition superior to 69% for all styles). We also provide acoustic characterization of the stimuli, depicting clear and contrasting acoustic profiles depending on the style of vocalization. All recordings are made freely available under a Creative Commons license and can be downloaded at https://osf.io/cgexn/ .
人类的嗓音具有显著的多样性，其声音会因使用方式的不同而有很大差异。越来越多的研究探讨了歌唱嗓音和说话嗓音之间的异同。然而，找到既受控制又具有生态效度的合适刺激材料具有挑战性，而且大多数数据集在同一嗓音所呈现的发声风格方面缺乏变异性。在此，我们描述了一个精心策划的发声刺激集，其中22名女歌手用三种截然不同的演唱风格（摇篮曲风格、流行歌曲风格和歌剧咏叹调风格）演唱了相同的旋律片段，并以两种说话风格（好像在和成年人说话或和婴儿说话）大声朗读了歌词。所有演唱均使用歌曲的原始歌词，采用巴西葡萄牙语，并带有/a/ /lu/音。这个包含1320次发声的具有生态效度的数据集通过一项强制选择实验室实验得到了验证（每种刺激有25名受试者），在该实验中，普通听众能够以较高的准确率识别出预期的发声风格（所有风格的正确识别比例均超过69%）。我们还提供了刺激材料的声学特征描述，展示了根据发声风格而清晰且截然不同的声学特征。所有录音均根据知识共享许可免费提供，可在https://osf.io/cgexn/ 下载。
