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This article considers machine methods used in the collection, processing, and application of vocal recordings for speaker identification and speech recognition between 1908 and 1970. The first phonographic archives featured collections of "vocal portraits" that prompted international investigations into the essential features of human voices for individual identification. Visual records of speech later found the same applications, but as "voiceprint identification" via sound spectrography began to achieve legal and commercial success in the 1960s, the procedure attracted more widespread scientific attention, which ultimately discredited both its accuracy and its rationale. At the same time, spectrogram collections spurred a new application-speech recognition by machine. The changing status of the speech spectrogram, from a record of unique features of individual voices to a model of fundamental invariants in speech sounds, was rooted in the demands of automated processing and a corresponding shift from the sound archive to the acoustic database.
Li et al. (2019) studied this question.