Science & Technology of Music and Sound (STMS), UMR 9912 (CNRS/IRCAM/UPMC), 1 place Stravinsky, 75004, Paris, France.
Inserm U 1127, CNRS UMR 7225, Sorbonne Universités UPMC Univ Paris 06 UMR S 1127, Institut du Cerveau et de la Moelle épinière (ICM), Social and Affective Neuroscience (SAN) Laboratory, Paris, France.
Behav Res Methods. 2018 Feb;50(1):323-343. doi: 10.3758/s13428-017-0873-y.
We present an open-source software platform that transforms emotional cues expressed by speech signals using audio effects like pitch shifting, inflection, vibrato, and filtering. The emotional transformations can be applied to any audio file, but can also run in real time, using live input from a microphone, with less than 20-ms latency. We anticipate that this tool will be useful for the study of emotions in psychology and neuroscience, because it enables a high level of control over the acoustical and emotional content of experimental stimuli in a variety of laboratory situations, including real-time social situations. We present here results of a series of validation experiments aiming to position the tool against several methodological requirements: that transformed emotions be recognized at above-chance levels, valid in several languages (French, English, Swedish, and Japanese) and with a naturalness comparable to natural speech.
我们提出了一个开源软件平台,该平台使用音高移动、语调、颤音和滤波等音频效果来转换语音信号所表达的情感提示。这些情感转换可以应用于任何音频文件,也可以使用麦克风的实时输入实时运行,延迟小于 20 毫秒。我们预计,该工具将对心理学和神经科学领域的情感研究非常有用,因为它能够在各种实验室情境中对实验刺激的声学和情感内容进行高度控制,包括实时社交情境。我们在此呈现一系列验证实验的结果,旨在根据以下方法学要求对该工具进行定位:转换后的情感识别率高于随机水平,在多种语言(法语、英语、瑞典语和日语)中有效,且自然度可与自然语音相媲美。