133 citations · 194 across the 40 of their papers we have counts for
43 papers
Environmental Sound Deepfake Detection Using Deep-Learning Framework
Khoi Vu, Dat Tran, Khanh Do +8
In this paper, we propose a deep-learning framework for Environmental Sound Deepfake Detection (ESDD) - the task of identifying whether the sound scene and sound event in an input…
A Toolchain for Comprehensive Audio/Video Analysis Using Deep Learning Based Multimodal Approach (A use case of riot or violent context detection)
Lam Pham, Phat Lam, Tin Nguyen +2
In this paper, we present a toolchain for a comprehensive audio/video analysis by leveraging deep learning based multimodal approach. To this end, different specific tasks of Speec…
Towards Unsupervised Speaker Diarization System for Multilingual Telephone Calls Using Pre-trained Whisper Model and Mixture of Sparse Autoencoders
Phat Lam, Lam Pham, Truong Nguyen +5
Existing speaker diarization systems typically rely on large amounts of manually annotated data, which is labor-intensive and difficult to obtain, especially in real-world scenario…
Deepfake Audio Detection Using Spectrogram-based Feature and Ensemble of Deep Learning Models
Lam Pham, Phat Lam, Truong Nguyen +2
In this paper, we propose a deep learning based system for the task of deepfake audio detection. In particular, the draw input audio is first transformed into various spectrograms…
The Impact of Frequency Bands on Acoustic Anomaly Detection of Machines using Deep Learning Based Model
Tin Nguyen, Lam Pham, Phat Lam +3
In this paper, we propose a deep learning based model for Acoustic Anomaly Detection of Machines, the task for detecting abnormal machines by analysing the machine sound. By conduc…
LSTM-based Deep Neural Network With A Focus on Sentence Representation for Sequential Sentence Classification in Medical Scientific Abstracts
Phat Lam, Lam Pham, Tin Nguyen +4
The Sequential Sentence Classification task within the domain of medical abstracts, termed as SSC, involves the categorization of sentences into pre-defined headings based on their…
Landslide Detection and Segmentation Using Remote Sensing Images and Deep Neural Network
Cam Le, Lam Pham, Jasmin Lampert +2
Knowledge about historic landslide event occurrence is important for supporting disaster risk reduction strategies. Building upon findings from 2022 Landslide4Sense Competition, we…
A Robust Deep Learning System for Motor Bearing Fault Detection: Leveraging Multiple Learning Strategies and a Novel Double Loss Function
Khoa Tran, Lam Pham, Vy-Rin Nguyen +1
Motor bearing fault detection (MBFD) is critical for maintaining the reliability and operational efficiency of industrial machinery. Early detection of bearing faults can prevent s…
Robust-MBDL: A Robust Multi-branch Deep Learning Based Model for Remaining Useful Life Prediction and Operational Condition Identification of Rotating Machines
Khoa Tran, Hai-Canh Vu, Lam Pham +1
In this paper, a Robust Multi-branch Deep learning-based system for remaining useful life (RUL) prediction and condition operations (CO) identification of rotating machines is prop…
A Deep Learning Architecture with Spatio-Temporal Focusing for Detecting Respiratory Anomalies
Dat Ngo, Lam Pham, Huy Phan +2
This paper presents a deep learning system applied for detecting anomalies from respiratory sound recordings. Our system initially performs audio feature extraction using Continuou…
Low-complexity deep learning frameworks for acoustic scene classification using teacher-student scheme and multiple spectrograms
Lam Pham, Dat Ngo, Cam Le +2
In this technical report, a low-complexity deep learning system for acoustic scene classification (ASC) is presented. The proposed system comprises two main phases: (Phase I) Train…
Deep Learning Based Multimodal with Two-phase Training Strategy for Daily Life Video Classification
Lam Pham, Trang Le, Cam Le +3
In this paper, we present a deep learning based multimodal system for classifying daily life videos. To train the system, we propose a two-phase training strategy. In the first tra…
An Inception-Residual-Based Architecture with Multi-Objective Loss for Detecting Respiratory Anomalies
Dat Ngo, Lam Pham, Huy Phan +3
This paper presents a deep learning system applied for detecting anomalies from respiratory sound recordings. Initially, our system begins with audio feature extraction using Gamma…
A Light-weight Deep Learning Model for Remote Sensing Image Classification
Lam Pham, Cam Le, Dat Ngo +4
In this paper, we present a high-performance and light-weight deep learning model for Remote Sensing Image Classification (RSIC), the task of identifying the aerial scene of a remo…
A Robust and Low Complexity Deep Learning Model for Remote Sensing Image Classification
Cam Le, Lam Pham, Nghia NVN +2
In this paper, we present a robust and low complexity deep learning model for Remote Sensing Image Classification (RSIC), the task of identifying the scene of a remote sensing imag…
Robust, General, and Low Complexity Acoustic Scene Classification Systems and An Effective Visualization for Presenting a Sound Scene Context
Lam Pham, Dusan Salovic, Anahid Jalali +4
In this paper, we present a comprehensive analysis of Acoustic Scene Classification (ASC), the task of identifying the scene of an audio recording from its acoustic signature. In p…
Remote Sensing Image Classification using Transfer Learning and Attention Based Deep Neural Network
Lam Pham, Khoa Tran, Dat Ngo +2
The task of remote sensing image scene classification (RSISC), which aims at classifying remote sensing images into groups of semantic categories based on their contents, has taken…
Low-complexity deep learning frameworks for acoustic scene classification
Lam Pham, Dat Ngo, Anahid Jalali +1
In this report, we presents low-complexity deep learning frameworks for acoustic scene classification (ASC). The proposed frameworks can be separated into four main steps: Front-en…
Wider or Deeper Neural Network Architecture for Acoustic Scene Classification with Mismatched Recording Devices
Lam Pham, Khoa Dinh, Dat Ngo +2
In this paper, we present a robust and low complexity system for Acoustic Scene Classification (ASC), the task of identifying the scene of an audio recording. We first construct an…
Audio-Based Deep Learning Frameworks for Detecting COVID-19
Dat Ngo, Lam Pham, Truong Hoang +2
This paper evaluates a wide range of audio-based deep learning frameworks applied to the breathing, cough, and speech sounds for detecting COVID-19. In general, the audio recording…
An Ensemble of Deep Learning Frameworks Applied For Predicting Respiratory Anomalies
Lam Pham, Dat Ngo, Truong Hoang +2
In this paper, we evaluate various deep learning frameworks for detecting respiratory anomalies from input audio recordings. To this end, we firstly transform audio respiratory cyc…
An Audio-Visual Dataset and Deep Learning Frameworks for Crowded Scene Classification
Lam Pham, Dat Ngo, Phu X. Nguyen +2
This paper presents a task of audio-visual scene classification (SC) where input videos are classified into one of five real-life crowded scenes: 'Riot', 'Noise-Street', 'Firework-…
An Annihilating Filter-Based DOA Estimation for Uniform Linear Array
Son Phan, Lam Pham
In this paper, we propose a new method to design an annihilating filter (AF) for direction-of-arrival (DOA) estimation of multiple snapshots within an uniform linear array. To eval…
A Cough-based deep learning framework for detecting COVID-19
Truong Hoang, Lam Pham, Dat Ngo +1
This paper presents a deep learning framework for detecting COVID-19 positive subjects from their cough sounds. In particular, the proposed approach comprises two main steps. In th…