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20212025
most citedSelf-Supervised Speaker Verification with Simple Siamese Network and Self-Supervised Regularization

6 citations · 8 across the 6 of their papers we have counts for

collaborators

6 papers

cs.RO2025

ROSAnnotator: A Web Application for ROSBag Data Analysis in Human-Robot Interaction

Yan Zhang, Haoqi Li, Ramtin Tabatabaei +1

Human-robot interaction (HRI) is an interdisciplinary field that utilises both quantitative and qualitative methods. While ROSBags, a file format within the Robot Operating System…

cs.SD2024

The NeurIPS 2023 Machine Learning for Audio Workshop: Affective Audio Benchmarks and Novel Data

Alice Baird, Rachel Manzelli, Panagiotis Tzirakis +7

The NeurIPS 2023 Machine Learning for Audio Workshop brings together machine learning (ML) experts from various audio domains. There are several valuable audio-driven ML tasks, fro…

eess.AS2023★ 2 cited

Zero-Shot End-to-End Spoken Language Understanding via Cross-Modal Selective Self-Training

Jianfeng He, Julian Salazar, Kaisheng Yao +2

End-to-end (E2E) spoken language understanding (SLU) is constrained by the cost of collecting speech-semantics pairs, especially when label domains change. Hence, we explore \texti…

eess.AS2022★ 6 cited

Self-Supervised Speaker Verification with Simple Siamese Network and Self-Supervised Regularization

Mufan Sang, Haoqi Li, Fang Liu +2

Training speaker-discriminative and robust speaker verification systems without speaker labels is still challenging and worthwhile to explore. In this study, we propose an effectiv…

eess.AS2021

Unsupervised Speech Representation Learning for Behavior Modeling using Triplet Enhanced Contextualized Networks

Haoqi Li, Brian Baucom, Shrikanth Narayanan +1

Speech encodes a wealth of information related to human behavior and has been used in a variety of automated behavior recognition tasks. However, extracting behavioral information…

cs.SD2021

Acted vs. Improvised: Domain Adaptation for Elicitation Approaches in Audio-Visual Emotion Recognition

Haoqi Li, Yelin Kim, Cheng-Hao Kuo +1

Key challenges in developing generalized automatic emotion recognition systems include scarcity of labeled data and lack of gold-standard references. Even for the cues that are lab…