Speaker anonymization
10 papers with code • 0 benchmarks • 0 datasets
Benchmarks
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Libraries
Use these libraries to find Speaker anonymization models and implementationsMost implemented papers
Speaker anonymization using neural audio codec language models
eurecom-asp/spk_anon_nac_lm
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The vast majority of approaches to speaker anonymization involve the extraction of fundamental frequency estimates, linguistic features and a speaker embedding which is perturbed to obfuscate the speaker identity before an anonymized speech waveform is resynthesized using a vocoder.
Anonymizing Speech: Evaluating and Designing Speaker Anonymization Techniques
The growing use of voice user interfaces has led to a surge in the collection and storage of speech data.
Speaker Anonymization with Distribution-Preserving X-Vector Generation for the VoicePrivacy Challenge 2020
In this paper, we present a Distribution-Preserving Voice Anonymization technique, as our submission to the VoicePrivacy Challenge 2020.
Speaker Anonymization with Phonetic Intermediate Representations
digitalphonetics/speaker-anonymization
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In this work, we propose a speaker anonymization pipeline that leverages high quality automatic speech recognition and synthesis systems to generate speech conditioned on phonetic transcriptions and anonymized speaker embeddings.
Anonymizing Speech with Generative Adversarial Networks to Preserve Speaker Privacy
digitalphonetics/speaker-anonymization
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In order to protect the privacy of speech data, speaker anonymization aims for hiding the identity of a speaker by changing the voice in speech recordings.
Vocoder drift in x-vector-based speaker anonymization
State-of-the-art approaches to speaker anonymization typically employ some form of perturbation function to conceal speaker information contained within an x-vector embedding, then resynthesize utterances in the voice of a new pseudo-speaker using a vocoder.
Long-term Conversation Analysis: Exploring Utility and Privacy
ol-mega/ppca
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The analysis of conversations recorded in everyday life requires privacy protection.
The Impact of Speech Anonymization on Pathology and Its Limits
tayebiarasteh/pathologyanonym
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This study investigates anonymization's impact on pathological speech across over 2, 700 speakers from multiple German institutions, focusing on privacy, pathological utility, and demographic fairness.
Probing the Feasibility of Multilingual Speaker Anonymization
digitalphonetics/speaker-anonymization
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In speaker anonymization, speech recordings are modified in a way that the identity of the speaker remains hidden.
Private kNN-VC: Interpretable Anonymization of Converted Speech
carlosfranzreb/private_knnvc
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Speaker anonymization seeks to conceal a speaker's identity while preserving the utility of their speech.
