Browsing by Author "Kucuk, Abdullah"
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Item Real Time Implementation of Direction of Arrival Estimation on Android Platforms for Hearing Aid Applications(2018-08) Kucuk, Abdullah; Panahi, Issa M. S.Sound Source Localization (SSL) is one of the vital areas in signal processing, especially in hearing aid applications. SSL (or Direction of Arrival) helps to determine the location of the speaker via multiple fixed microphones (also known as microphone array). Knowing of speaker Direction of Arrival (DOA) helps to improve the performance of the system. Another advantage of DOA is that it helps hearing-impaired people to locate talker because hearing aid users, especially those who are older than 60 years, have difficulties in determining the place of the speaker. Having requisite processing capabilities and at least two microphones makes smartphones a cost-effective solution for multi-channel audio signal processing. In this thesis, we propose a new stereo input/output framework for Android platforms for audio signal processing. This frame enables us to perform multi or single channel audio signal processing for real-time operations. We also propose a method for two microphones-based Direction of Arrival (DOA) estimation and real-time implementation of this method on the latest Android smartphones.Item Real-Time Smartphone Implementation of Noise-Robust Speech Source Localization Algorithm for Hearing Aid Users(Acoustical Society of America) Ganguly, Anshuman; Kucuk, Abdullah; Panahi, Issa; Ganguly, Anshuman; Kucuk, Abdullah; Panahi, IssaSpeech source localization has numerous application areas such as hearing aid devices (HAD) and consumer electronics applications. Utilizing the powerful processing hardware of smartphones, we demonstrate that smartphones are capable of instantaneous estimation of sound location. In this paper, we present instantaneous direction of arrival (DOA) by using traditional Generalized Cross Correlation (GCC) followed by a spatial post-filtering stage. A simple voice activity detector (VAD) is used for the post-filtering stage to improve noise robustness in some realistic reverberant noisy environments. Root mean square error (RMSE) is used as an evaluation criterion for the proposed method. Both real recorded data and simulated data under different noise types are used for experiments. A real-time implementation of the method on an Android-based smartphone is also presented.Item Sound Source Localization for Improving Hearing Aid Studies Using Mobile Platforms(December 2021) Kucuk, Abdullah; Panahi, Issa M.S.; Ntafos, Simeon; Busso, Carlos; Nourani, Mehrdad; Nosratinia, AriaMicrophone array is one of the powerful techniques that enables to apply effective signal processing algorithms to systems. One of the critical application areas of microphone array is sound source localization (SSL), which refers to identify the speaker of interest using a microphone array. SSL can be used as a preprocessing technique to boost up the entire system efficiency. Recent studies show that smartphones can be an efficient assistive device for hearing aid devices because of smartphones’ powerful hardware and software components. Also, Deep Learning (DL) has shown a considerable performance increase in audio signal processing. DL based SSL using the direction of arrival estimation (DOA) methods for two and eight microphone array structures and the distance estimation methods using a single microphone are proposed in this work. The performance of the proposed methods are evaluated in several realistic noisy conditions, reverberations using real-recorded data. Another contribution of this work is to present real-time implementations of the DL based methods on edges devices, i.e., smartphones, tablets.