  Voice-based human-machine interfaces with an automatic speaker verification
(ASV) component are commonly used in the market. However, the threat from
presentation attacks is also growing since attackers can use recent speech
synthesis technology to produce a natural-sounding voice of a victim.
Presentation attack detection (PAD) for ASV, or speech anti-spoofing, is
therefore indispensable. Research on voice PAD has seen significant progress
since the early 2010s, including the advancement in PAD models, benchmark
datasets, and evaluation campaigns. This chapter presents a practical guide to
the field of voice PAD, with a focus on logical access attacks using
text-to-speech and voice conversion algorithms and spoofing countermeasures
based on artifact detection. It introduces the basic concept of voice PAD,
explains the common techniques, and provides an experimental study using recent
methods on a benchmark dataset. Code for the experiments is open-sourced.
