Title: Speaker Recognition with Cough, Laugh and "Wei",
Abstract: This paper proposes a speaker recognition (SRE) task with trivial speech
events, such as cough and laugh. These trivial events are ubiquitous in
conversations and less subjected to intentional change, therefore offering
valuable particularities to discover the genuine speaker from disguised speech.
However, trivial events are often short and idiocratic in spectral patterns,
making SRE extremely difficult. Fortunately, we found a very powerful deep
feature learning structure that can extract highly speaker-sensitive features.
By employing this tool, we studied the SRE performance on three types of
trivial events: cough, laugh and "Wei" (a short Chinese "Hello"). The results
show that there is rich speaker information within these trivial events, even
for cough that is intuitively less speaker distinguishable. With the deep
feature approach, the EER can reach 10%-14% with the three trivial events,
despite their extremely short durations (0.2-1.0 seconds).