Shahab PashaUniversity of Wollongong | UOW · School of Electrical, Computer and Telecommunications Engineering (SECTE)
Doctor of Philosophy
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Citations since 2017
14 Research Items
Current research topics include ad-hoc signal processing and feature extraction from acoustic signals. Applying deep learning methods to the spatial recordings independent of the microphone type is the current project.
July 2017 - January 2019
ARC steel research hub
- Research Associate
This paper reports on the implementation of a multi-channel electronic stethoscope designed to isolate the heart sound from the interfering sounds of the lungs and blood vessels. The multi-channel stethoscope comprises four piezo contact microphones arranged in rectangular and linear arrays. Beamforming and channel equalisation techniques are appli...
Given ubiquitous digital devices with recording capability, distributed microphone arrays are emerging recording tools for hands-free communications and spontaneous tele-conferencings. However, the analysis of signals recorded with diverse sampling rates, time delays, and qualities by distributed microphone arrays is not straightforward and entails...
This paper describes an artificial-intelligence-assisted screening system implemented to support medical cardiovascular examinations performed by doctors. The proposed system is a two-stage supervised classifier comprising a convolutional neural network for heart murmur detection and a decision tree for classifying vital signs. The classifiers are...
In an era of ubiquitous digital devices with built-in microphones and recording capability, distributed microphone arrays of a few digital recording devices are the emerging recording tool in hands-free speech communications and immersive meetings. Such so-called ad hoc microphone arrays can facilitate high-quality spontaneous recording experiences...
This paper proposes the use of deep learning classification for acoustic monitoring of an industrial process. Specifically, the application is to process sound recordings to detect when additional air leaks through gaps between grate bars lining the bottom of the sinter strand pallets, caused by thermal cycling, aging and deterioration. Detecting h...
A spatially modified multi-channel linear prediction analysis is proposed and tested for the dereverberation of ad-hoc microphone arrays. The proposed spatial multi-channel linear prediction takes into account the estimated spatial distances between each microphone and the source and is applied for the short-term dereverberation (pre-whitening). Th...
This paper proposes the use of the frequency domain Magnitude Squared Coherence (MSC) between two ad-hoc recordings of speech as a reliable speaker discrimination feature for source counting applications in highly reverberant environments. The proposed source counting method does not require knowledge of the microphone spacing and does not assume a...
Ad-hoc microphone arrays formed from the microphones of mobile devices such as smart phones, tablets and notebooks are emerging recording platforms for meetings, press conferences and other sound scenes. As opposed to the Wireless Acoustic Sensor Networks (WASN), ad-hoc microphones do not communicate within the array and location of each microphone...
Coherent-to-diffuse ratio (CDR) estimates over short time frames are utilized for source counting using ad-hoc microphone arrays to record speech from multiple participants in scenarios such as a meeting. It is shown that the CDR estimates obtained at ad-hoc dual (two channel) microphone nodes, located at unknown locations within an unknown reverbe...
This paper proposes a novel approach to detecting multiple, simultaneous talkers in multi-party meetings using localisation of active speech sources recorded with an ad-hoc microphone array. Cues indicating the relative distance between sources and microphones are derived from speech signals and room impulse responses recorded by each of the microp...
A novel unsupervised multi-channel dereverberation approach in ad-hoc microphone arrays context based on removing microphones with relatively higher level of reverberation from the array and applying the dereverberation method on a subset of microphones with lower level of reverberation is proposed in this paper. This approach does not require any...
This paper investigates the formation of ad-hoc microphone arrays for the purpose of recording multiple sound sources by clustering microphones spatially distributed within a room. A novel codebook-based unsupervised method for cluster formation using features derived from the Room Impulse Responses (RIRs) corresponding to each microphone is propos...
In real-time packet-based communication systems, one major problem is misrouted or delayed packets which results in degraded perceived voice quality. If packets are not available on time, the packet is known as lost packet. The easiest task of a network terminal receiver is to replace silence for the duration of lost speech segments. In a high qual...
I am working on an AI project where I am using C++ and Tensor flow functions. Is there a way to combine them together using Edge impulse?
I am collecting a heart sound database for my research. I am undecided about the electronic stethoscope I want to use. There are Piezoelectric stethoscopes which seem to be more robust to the noise however capacitor transducer stethoscopes look more accurate. Is there a real difference?
I am using a phase shift acoustic beamformer for interference suppression by a ULA. I was wondering if there is a better way.
This project is aiming at implementation of a deep-learning classifier for detection of heart issues by analysing the heart sound recordings.