Topic: voice recognition

The goal of this pilot study is to develop a test through which people with extraordinary voice recognition and discrimination skills can be found (for forensic purposes). Since interest in this field has emerged, three studies have been published with the goal of finding people with potential super-recognition skills in voice processing. One of them is a discrimination test and two are recognition tests, but neither combines the two test scenarios and their test designs cannot be directly compared to a casework scenario in forensics phonetics. The pilot study at hand attempts to bridge this g

The cortical algorithm hypothesis states that there is one common computational framework to solve diverse cognitive problems such as vision, voice recognition and motion control. In my talk, I propose a strategy to guide the search for this algorithm and I present a few ideas on how some of its components might look like. I'll explain why a highly interdisciplinary approach is needed from neuroscience, computer science, mathematics and physics to make further progress in this important question.

The ability to recognize someone’s voice spans a broad spectrum with phonagnosia on the low end and super recognition at the high end. Yet there is no standardized test to measure the individual ability to learn and recognize newly-learnt voices with samples of speech-like phonetic variability. We have developed the Jena Voice Learning and Memory Test (JVLMT), a 20 min-test based on item response theory and applicable across different languages. The JVLMT consists of three phases in which participants are familiarized with eight speakers in two stages and then perform a three-alternative force