A Microphone Array and Voice Algorithm based Smart Hearing Aid

Abstract

Approximately 6.2% of the world's population (466 million people) suffer from disabling hearing impairment [1]. Hearing impairment impacts negatively on one's education, financial success [2] [3], cognitive development in childhood [4], including increased risk of dementia in older adulthood [5]. Lack of or reduced social interaction due to hearing impairment affects creating or maintaining healthy relationships at home, school and work [5]. Hence, hearing impairment genuinely affects the overall quality of life and wellbeing. The cocktail party effect, which is a healthy hearing individual's ability to understand one voice in a cacophony of other voices or sounds, is an important ability lacking in people with hearing impairment. This inability results in difficulties with simple daily activities such as partaking in group discussions or conversing in noisy restaurants [6]. This smart hearing aid aims to provide much-needed assistance with understanding speech in noisy environments. For example, if a person wants to partake in a group discussion, he/she needs to place the microphone array based unit on a flat surface in front of him/her, such as a table. When conversations take place, the microphone array will capture and process sound from all directions, intelligently prioritise and provide the lead speaker's voice by suppressing unwanted noises, including speeches of other people. This device selects and alternates voices between speakers automatically using voice algorithms. Additionally, the user has the option of further fine-tuning the acoustic parameters as needed through a smartphone interface. This paper describes the development and functions of this new smart hearing aid.

Communication Requirements in 5G-Enabled Healthcare Applications: Review and Considerations

“…Patients with underlying conditions or those who need assisted living in chronic scenarios can benefit from applications for measuring and reporting electroencephalogram (EEG) [ 102 , 103 ], ECG [ 93 , 104 , 105 ], electromyography (EMG) [ 106 , 107 ] heart rate [ 108 , 109 , 110 ] for cardiac patients, glucose [ 111 , 112 ], insulin for diabetic patients [ 113 , 114 , 115 ], and continuous respiratory rate for chronic respiratory patients [ 116 ]. For assisting the physically impaired, there are numerous wearable devices to help improve quality of life, such as hearing aids (ear-to-ear communication) [ 117 , 118 ]; devices for disability assistance, e.g., muscle tension monitor [ 119 ]; muscle tension stimulation [ 120 ]; wearable assistive devices for the blind [ 121 , 122 , 123 , 124 ]; devices for speech impairment [ 125 , 126 ]; artificial/wearable limbs [ 127 , 128 , 129 ]; and exoskeleton suits [ 130 ]. Other examples that can be used by the elderly, or by Alzheimer’s or epilepsy patients, include wearables for fall detection [ 131 , 132 , 133 ] and seizure detection [ 134 , 135 ], and gyroscopes [ 136 ] and accelerometers [ 137 ] for localization monitoring.…”

A Report on the Cost of Data Privacy

“…Such heterogeneous systems consist of a combination of multiple processors and chipsets. For example, in the Smart Hearing Aid prototype from [9], the users have integrated a DSP-based microphone array with a Linux SBC to perform edge level audio processing such as noise suppression, the direction of arrival estimation, etc., without depending on the internet. The IoT devices can be power efficient when the user assigns different workloads to the most efficient compute engine [16].…”

Unsupervised Method to Analyze Playing Styles of EPL Teams using Ball Possession-position Data

“…We also plan to apply other methods such as Kernelbased SVRs [18], CNNs [19], One-Class Classifiers [20], SVMs [21], and DNNs [22]- [24] on the dataset.…”