Voice spoofing detector: A unified anti-spoofing framework

Anti-spoofing, Voice Databases

As with any task involving statistical pattern recognition, the assessment of spoofing and anti-spoofing approaches for voice recognition calls for significantscale databases of spoofed speech signals. Depending on the application, these signals should normally reflect spoofing attacks performed prior to acquisition at the sensor or microphone. Since the collection of large quantities of any bi...

Anti-spoofing, Voice

The process of verifying whether the voice sample presented to an authentication system is real (i.e., alive), or whether it is replayed or synthetic, and thus fraudulent. When authentication through a voice authentication system is requested, it is important to be sure that the person seeking the authentication actually provides the required voice sample at the time and place of the authentica...

Anti-spoofing, Voice Conversion

Voice conversion is a process which converts or transforms one speaker’s voice towards that of another. The literature shows that voice conversion can be used to spoof or fool an automatic speaker verification system. State-of-the-art voice conversion algorithms can produce high-quality speech signals in real time and are capable of fooling both human listeners and automatic systems, including ...

Spoofing and Anti-Spoofing Measures

Speaker Recognition Anti-spoofing

Progress in the development of spoofing countermeasures for automatic speaker recognition is less advanced than equivalent work related to other biometric modalities. This chapter outlines the potential for even state-of-the-art automatic speaker recognition systems to be spoofed. While the use of a multitude of different datasets, protocols and metrics complicates the meaningful comparison of ...