ISS 3.1: Intelligent ear-level devices for hearing enhancement and health and wellness monitoring

With resurgence of artificial intelligence (AI) and machine learning, sensor miniaturization and increased wireless connectivity, ear-level hearing devices are going through a major revolution transforming themselves from traditional hearing aids into modern hearing enhancement and health and wellness monitoring devices. For the aging user population of hearing aids, sound quality and speech understanding in challenging listening environments remain unsatisfactory. To improve quality of life and reduce health care cost, it is highly desirable if the devices can provide effective health and wellness monitoring capability on a continuous basis in everyday life. Finally, as the device functionality becomes more complex and dexterity is a major challenge for our user population, easy and intuitive user interactions with the devices are becoming increasingly important. In this talk, we will present examples of such transformation in the areas of hearing enhancement, health and wellness monitoring and user experience. In the process, we will highlight how AI and machine learning, miniaturized sensors and wireless connectivity are enabling and accelerating the transformation. In addition, we will discuss practical challenges for the transformation in areas of power consumption, non-volatile and volatile storage, audio latency and wireless reliability. Finally, we will provide an outlook on future directions and opportunities for intelligent ear-level devices.

Speaker: Dr. Tao Zhang, Ph.D., Director of Algorithms , Starkey Hearing Technologies, USA

ISS 3.2: Digitization of Urban Sound in a Smart Nation

In this digital era, sensing and processing are being integrated into IoT devices that can be easily and economically deployed in our urban environment. In this talk, the speaker will describe some of the digital sound and active noise mitigation technologies that have been developed in my lab and some pilot deployment in our urban environment. In order to achieve a holistic understanding of our urban environment, we must rely on intelligent sound sensing that can operate 24/7 and deploy widely under different environmental conditions. These intelligent sound sensors also serve as digital ears to complement and activates the digital eyes of the CCTV cameras. By having a comprehensive and big aural sound data allows public agencies to better formulate complete and accurate sound mitigation policies. Sound pressure level (SPL) readings have been the de facto standard in quantifying our noise environment; however, SPL alone cannot accurately indicate how humans actually perceive noise; whether they like or dislike the sound even at the same SPL. The latest ISO standards (i.e. ISO 12913-1:2014, ISO 12913-2:2018) have been moving towards a measurement that is based on how humans perceive sound. With the advent of powerful and low-cost embedded processors, analog-to-digital convertors, and acoustic sensors, we are now seeing wide-spread usage of digital active noise control (ANC) technologies in consumer products, like hearables and in automobiles. In this talk, the speaker will also showcase our latest work in extending active noise control applications to a larger region of control, such as in open windows and openings of noise sources. Digitization plays a key role in advancing the art of ANC to incorporate artificial intelligence to select the most annoying noise to cancel and provide ways to further mitigate noise by perceptual-based sound augmentation.

Speaker: Dr.Woon-Seng Gan, Director of Smart Nation Lab at Nanyang Technological University, Singapore

ISS 3.3: Mechanical Noise Suppression: Debutant of phase in signal enhancement after 30 years of silence

This talk presents challenges, solutions, and applications in commercial products of mechanical noise suppression. The topic has become more important as dissemination of consumer products that process environmental signals in addition to human speech. Three typical types of mechanical noise signals with small, medium, and large signal power, represented by feature phones and camcorders, digital cameras, and standard and tablet PCs, respectively, are covered. Mechanical noise suppression for small power signals is performed by continuous spectral template subtraction with a noise template dictionary. Medium power mechanical noise is suppressed in a similar manner only when its presence is notified by the parent system such as the digital camera. When the power is large, explicit detection of the mechanical noise based on phase information determines suppression timings. In the all three scenarios, the phase information of the input noisy signal is randomized for making the residual noise inaudible in frequency bins where noise is dominant. The phase has been unaltered in the past 30 years after Lim, thus, these suppression algorithms opened the door to a new signal enhancement era. Sound demonstrations before and after suppression highlight the effect of the algorithms and make the talk engaging.

Speaker: Dr. Akihiko K. Sugiyama, IEEE Fellow. Yahoo! JAPAN Research, Yahoo Japan

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