Vocal recognition before recording: techniques of vocal documentation, classification and identification in the long nineteenth century

IF 0.4 0 HUMANITIES, MULTIDISCIPLINARY
J. Hoegaerts
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引用次数: 0

Abstract

ABSTRACT This paper aims to sketch out a cultural history of documenting, classifying and identifying voices in the nineteenth century. Focusing on a period before technologies like the spectogram became widely available, I demonstrate that experts in this period already harboured many of the ideas and ambitions that would later drive the development of technologies in speech recognition and the voiceprint. First, the idea that each human voice was unique – and therefore individual – was thoroughly developed in. Secondly, various embodied techniques for the description, comparison and recognition of particular voices were developed throughout the century, mobilising both the human ear and visual aids. Drawing on insights from the fields of voice studies and sound studies, and based on scientific, pedagogical, and musical expertise formulated and circulated in Britain, France, and Germany in the nineteenth century, the paper teases out the trajectory of these techniques, and changing vocabularies of vocal uniqueness. Central to the idea that voices were “as different from each other as faces”, were cultural assumptions about distinctions between different (European) national, cultural, and gendered voices, making the pre-history of speech recognition a cultural history, as much as it is a history of science or technology.
录音前的声音识别:在漫长的19世纪的声音记录、分类和识别技术
本文旨在勾勒出19世纪记录、分类和识别声音的文化史。我把重点放在像频谱图这样的技术广泛应用之前的一段时间里,证明了这一时期的专家们已经有了许多想法和抱负,这些想法和抱负后来推动了语音识别和声纹技术的发展。首先,每个人的声音都是独一无二的,因此是独立的,这一观点在1980年得到了彻底的发展。其次,整个世纪发展了各种具体技术,用于描述、比较和识别特定的声音,调动了人耳和视觉辅助。根据声音研究和声音研究领域的见解,并基于19世纪在英国、法国和德国制定和传播的科学、教学和音乐专业知识,本文梳理了这些技术的发展轨迹,以及声乐独特性的变化词汇。声音“就像面孔一样彼此不同”这一观点的核心,是关于不同(欧洲)民族、文化和性别声音之间差异的文化假设,这使得语音识别的史前历史成为一部文化史,就像它是一部科学或技术史一样。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Sound Studies
Sound Studies HUMANITIES, MULTIDISCIPLINARY-
CiteScore
1.30
自引率
0.00%
发文量
24
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