When you first hear about Audio and Acoustic Signal Processing (AASP) it’s likely you don’t think of the movies, music and modern smartphones that it gives life to. As a sub-category of signal processing, AASP specifically deals with the analysis, processing and synthesis of sound that has been either recorded by one or more microphones or artificially generated by, for example, a computer program or synthesizer.
PhD Student, Glasgow Caledonian University
Signal processing is exploited in daily industrial applications for analysis purposes, particularly in the power generation field. Consider the example of a high voltage power supply site – a plant that contains power generators and transformers. Such systems are susceptible to Electro-Magnetic Interference (EMI), produced during the operation of the system or due to fault occurrence.
As every year, this past November saw the election of new members to the Speech and Language Technical Committee to take the places of those whose 3-year terms are coming to an end. SLTC membership is grouped by subject area, and in this year’s election (for the 2017-2019 term) we had 17 openings in 8 areas. Current members are eligible to run for a consecutive term once.
This welcome message marks the start of the new year and comes at the tail end of a several months long busy period of the SLTC. First of all, there is the yearly election cycle, carefully administered by our election sub-committee. Please join me in thanking 12 member who retired their position at the end of 2016: Tomoki Toda, Gernot Kubin, Maurizio Omologo, Nicholas Evans, Larry Heck, Peder Olsen, Frank Seide, Mark Hasegawa-Johnson, Deep Sen, Svetlana Stoyanchev, Jasha Droppo and George Saon. And please join me in welcoming the class of 2019.
Kush R. Varshney, research staff member and manager in the Data Science Group at the IBM Thomas J. Watson Research Center.
Communication, speech processing, seismology and radar are well-known applications of signal processing that contribute to the betterment of humanity. But is there a more direct way that signal and information processing can reduce poverty, hunger, inequality, injustice, ill health and other causes of human suffering?