This review article is concerned with metamaterials, i.e. specifically engineered structures with special properties for interaction with sounds. The research on and practical design of these materials have gained momentum in the last decade, when 3D printing techniques provided the possibility to fabricate such geometrically complex structures. We briefly describe the history of research on AMMs and group them into active and passive metamaterials. For each of these groups of AMMs, we discuss the most notable construction achievements and outline the main applications. We conclude this review with a discussion of possible directions for further research and main applications of AMMs such as noise attenuation, acoustic lens, and the cloaking phenomenon.

The presented review discusses recent research on human echolocation by blind and sighted subjects, aiming to classify and evaluate the methodologies most commonly used when testing active echolocation methods. Most of the reviewed studies compared small groups of both blind and sighted volunteers, although one in four studies used sighted testers only. The most common trial procedure was for volunteers to detect or localize static obstacles, e.g., discs, boards, or walls at distances ranging from a few centimeters to several meters. Other tasks also included comparing or categorizing objects. Few studies utilized walking in real or virtual environments. Most trials were conducted in natural acoustic conditions, as subjects are marginally less likely to correctly echolocate in anechoic or acoustically dampened rooms. Aside from live echolocation tests, other methodologies included the use of binaural recordings, artificial echoes or rendered virtual audio. The sounds most frequently used in the tests were natural sounds such as the palatal mouth click and finger snapping. Several studies have focused on the use of artificially generated sounds, such as noise or synthetic clicks. A promising conclusion from all the reviewed studies is that both blind and sighted persons can efficiently learn echolocation.