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Found 18 papers, 5 papers with code
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.
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.
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.
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.
