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Adjustable Deterministic Pseudonymization of Speech Listening Experiment, Report of listening experiments

Authors: Son, Rob Van;

Adjustable Deterministic Pseudonymization of Speech Listening Experiment, Report of listening experiments

Abstract

A method for the pseudonymization of speech is presented that allows to obfuscate the identity of a speaker in untranscribed running speech. The approach is to manipulate the spectro- temporal structure of the speech to simulate a different length and structure of the vocal tract, as well as a different pitch and speaking rate. The method is deterministic, and partially re- versible. The extend of the changes is adjustable and gradual. A series of ABX listening experiments show that both experts and non-experts identify speakers in less than 70% of forced choice pairs while listeners are able to identify over 90% of speak- ers without pseudonymization. Reverting the procedure, de- pseudonymization, is partially effective. Some pseudonymiza- tion targets, e.g., those simulating a long vowel tract, are more amenable to de-pseudonymization than others. The method also works differently on female and male voices. Depending on the pseudonymization target, female speakers were less well iden- tified after pseudonymization and de-pseudonymization than male speakers.

Keywords

speech pseudonymization, human speaker identification

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This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
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influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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