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The health care industry may seem the ideal place to deploy artificial intelligence systems. Each medical test, doctor’s visit, and procedure is documented, and patient records are increasingly stored in electronic formats. AI systems could digest that data and draw conclusions about how to provide better and more cost-effective care. Plenty of researchers are building such systems:
Five years ago, engineers at NASA started to think about using a large number of electric motors to create a blown wing, later naming the project LEAPTech, for Leading Edge Asynchronous Propeller Technology. The novel configuration was based on an old concept: The idea—known as a “blown wing”—was to propel air at high speed over the wing using many motors and propellers mounted along the leading edge.
In today’s big and messy data age, there is a lot of data generated everywhere around us. Examples include texts, tweets, network traffic, changing Facebook connections, or video surveillance feeds coming in from one or multiple cameras. Dimension reduction and noise/outlier removal are usually important preprocessing steps before any high-dimensional (big) data set can be used for inference.
Speaker age and gender classification is one of the most challenging problems in speech processing. Recently with developing technologies, identifying a speaker age and gender has become a necessity for speaker verification and identification systems such as identifying suspects in criminal cases, improving human-machine interaction, and adapting music for awaiting people queue.
In patent no 9,852,740 a high quality speech is reproduced with a small data amount in speech coding and decoding for performing compression coding and decoding of a speech signal to a digital signal.
Our heartiest congratulations to Mari Ostendorf, winner of the 2017 SPS Meritorious Service Award “for exemplary service to and leadership in the Signal Processing Society.” Mari’s service to SPS has included membership many SPS committees, including the Speech Processing Technical Committee (1990-93), the SPS DSP Education Committee (1992-93), the SPS Awards Committee (2009, 2015) and the SPS Awards Board (2015-2016), the SPS Executive Committee (2012-2014). She also served on the SPS Board of Governors (2009-2014) and was Vice President for Publications for SPS (2012-2014).&nb
The 2017 IEEE Automatic Speech Recognition and Understanding Workshop (ASRU 2017) was held on December 16-20, 2017 in Okinawa, a southern island of Japan.
The workshop gathered the record number of participants (271 registrations, 48% from industry and 47% from academia). The workshop featured 4 keynote speech and 6 invited talks, some of which are outlined in more detail below.
This April at ICASSP, Alejandro (Alex) Acero will receive the Society Award from IEEE Signal Processing Society for "contributions to speech technology and leadership in the signal processing community." The Society Award is the highest honor awarded by the Signal Processing Society, and it honors members who have demonstrated both outstanding technical contributions in the signal processing field and outstanding leadership to the society.
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The IEEE Signal Processing Society is dedicated to supporting the professional growth and career advancement of its members in the dynamic field of signal processing. Learn More
Signal processing education and professional development program for all career levels. Learn more.