With advances seen in deep learning, voice-based applications are burgeoning, ranging
from personal assistants, affective computing, to remote disease diagnostics. As the voice …

With advances seen in deep learning, voice-based applications are burgeoning, ranging
from personal assistants, affective computing, to remote disease diagnostics. As the voice …

Automated voice anonymization algorithms are used to obfuscate speaker identity while
leaving other vocal attributes untouched; they have been used for eg, speech recognition …

In an age of voice-enabled technology, voice anonymization offers a solution to protect
people's privacy, provided these systems work equally well across subgroups. This study …

In this paper, we propose a voice anonymization framework based on data-driven
optimization of cascaded voice modification modules. With increasing opportunities to use …

Voice-based human-computer interaction has become pervasive in laptops, smartphones,
home voice assistants, and Internet of Thing (IoT) devices. However, voice interaction comes …

Speaker anonymization is the task of modifying a speech recording such that the original
speaker cannot be identified anymore. Since the first Voice Privacy Challenge in 2020 …

The growing use of voice user interfaces has led to a surge in the collection and storage of
speech data. While data collection allows for the development of efficient tools powering …

Integration of speech into healthcare has intensified privacy concerns due to its potential as
a non-invasive biomarker containing individual biometric information. In response, speaker …

Speech data carries a range of personal information, such as the speaker's identity and
emotional state. These attributes can be used for malicious purposes. With the development …