Search Results for author:
Found 29 papers, 8 papers with code
Multi-modal Speech Enhancement with Limited Electromyography Channels
Speech enhancement (SE) aims to improve the clarity, intelligibility, and quality of speech signals for various speech enabled applications.
XLSR-Mamba: A Dual-Column Bidirectional State Space Model for Spoofing Attack Detection
Transformers and their variants have achieved great success in speech processing.
Leveraging LLM and Text-Queried Separation for Noise-Robust Sound Event Detection
Sound Event Detection (SED) is challenging in noisy environments where overlapping sounds obscure target events.
Ranked #1 on
Sound Event Detection
on WildDESED
(using extra training data)
Exploring Text-Queried Sound Event Detection with Audio Source Separation
To address this issue, we propose the text-queried SED (TQ-SED) framework.
TF-Mamba: A Time-Frequency Network for Sound Source Localization
We consider the Mamba-based model to analyze spatial features from speech signals by fusing both time and frequency features, and we develop an SSL system called TF-Mamba.
Configurable DOA Estimation using Incremental Learning
This study introduces a progressive neural network (PNN) model for direction of arrival (DOA) estimation, DOA-PNN, addressing the challenge due to catastrophic forgetting in adapting dynamic acoustic environments.
Mixstyle based Domain Generalization for Sound Event Detection with Heterogeneous Training Data
This work explores domain generalization (DG) for sound event detection (SED), advancing adaptability towards real-world scenarios.
WildDESED: An LLM-Powered Dataset for Wild Domestic Environment Sound Event Detection System
This work aims to advance sound event detection (SED) research by presenting a new large language model (LLM)-powered dataset namely wild domestic environment sound event detection (WildDESED).
Ranked #3 on
Sound Event Detection
on WildDESED
UCIL: An Unsupervised Class Incremental Learning Approach for Sound Event Detection
This work explores class-incremental learning (CIL) for sound event detection (SED), advancing adaptability towards real-world scenarios.
FMSG-JLESS Submission for DCASE 2024 Task4 on Sound Event Detection with Heterogeneous Training Dataset and Potentially Missing Labels
Our proposed method shows superior macro-average pAUC and polyphonic SED score performance on the DCASE 2024 Challenge Task 4 validation dataset and public evaluation dataset.
How Do Neural Spoofing Countermeasures Detect Partially Spoofed Audio?
Recent work shows that countermeasures (CMs) trained on partially spoofed audio can effectively detect such spoofing.
Face-voice Association in Multilingual Environments (FAME) Challenge 2024 Evaluation Plan
The Face-voice Association in Multilingual Environments (FAME) Challenge 2024 focuses on exploring face-voice association under a unique condition of multilingual scenario.
Enhancing Real-World Active Speaker Detection with Multi-Modal Extraction Pre-Training
Audio-visual active speaker detection (AV-ASD) aims to identify which visible face is speaking in a scene with one or more persons.
Active Speaker Detection
Audio-Visual Active Speaker Detection
+2
Dual Knowledge Distillation for Efficient Sound Event Detection
To address this issue, we introduce a novel framework referred to as dual knowledge distillation for developing efficient SED systems in this work.
Ranked #2 on
Sound Event Detection
on DESED
(using extra training data)
Adaptive-avg-pooling based Attention Vision Transformer for Face Anti-spoofing
In this work, we propose a novel vision transformer referred to as adaptive-avg-pooling based attention vision transformer (AAViT) that uses modules of adaptive average pooling and attention to replace the module of average value computing.
A Multi-Task Learning Framework for Sound Event Detection using High-level Acoustic Characteristics of Sounds
Sound event detection (SED) entails identifying the type of sound and estimating its temporal boundaries from acoustic signals.
Leveraging Audio-Tagging Assisted Sound Event Detection using Weakified Strong Labels and Frequency Dynamic Convolutions
Stage-1 of our proposed framework focuses on audio-tagging (AT), which assists the sound event detection (SED) system in Stage-2.
I4U System Description for NIST SRE'20 CTS Challenge
This manuscript describes the I4U submission to the 2020 NIST Speaker Recognition Evaluation (SRE'20) Conversational Telephone Speech (CTS) Challenge.
Self-Supervised Training of Speaker Encoder with Multi-Modal Diverse Positive Pairs
We study a novel neural architecture and its training strategies of speaker encoder for speaker recognition without using any identity labels.
MFA: TDNN with Multi-scale Frequency-channel Attention for Text-independent Speaker Verification with Short Utterances
The time delay neural network (TDNN) represents one of the state-of-the-art of neural solutions to text-independent speaker verification.
HLT-NUS SUBMISSION FOR 2020 NIST Conversational Telephone Speech SRE
This work provides a brief description of Human Language Technology (HLT) Laboratory, National University of Singapore (NUS) system submission for 2020 NIST conversational telephone speech (CTS) speaker recognition evaluation (SRE).
Self-supervised Speaker Recognition with Loss-gated Learning
In self-supervised learning for speaker recognition, pseudo labels are useful as the supervision signals.
Significance of Data Augmentation for Improving Cleft Lip and Palate Speech Recognition
The automatic recognition of pathological speech, particularly from children with any articulatory impairment, is a challenging task due to various reasons.
Is Someone Speaking? Exploring Long-term Temporal Features for Audio-visual Active Speaker Detection
Active speaker detection (ASD) seeks to detect who is speaking in a visual scene of one or more speakers.
Active Speaker Detection
Audio-Visual Active Speaker Detection
NUS-HLT Report for ActivityNet Challenge 2021 AVA (Speaker)
Active speaker detection (ASD) seeks to detect who is speaking in a visual scene of one or more speakers.
Active Speaker Detection
Audio-Visual Active Speaker Detection
Speaker-Utterance Dual Attention for Speaker and Utterance Verification
The proposed SUDA features an attention mask mechanism to learn the interaction between the speaker and utterance information streams.
LONG RANGE ACOUSTIC AND DEEP FEATURES PERSPECTIVE ON ASVSPOOF 2019
In this paper, we summarize the findings from the perspective of long range acoustic and deep features for spoof detection.
I4U Submission to NIST SRE 2018: Leveraging from a Decade of Shared Experiences
The I4U consortium was established to facilitate a joint entry to NIST speaker recognition evaluations (SRE).
Generative x-vectors for text-independent speaker verification
Speaker verification (SV) systems using deep neural network embeddings, so-called the x-vector systems, are becoming popular due to its good performance superior to the i-vector systems.
