6 citations · 15 across the 14 of their papers we have counts for
14 papers
SLM-TTA: A Framework for Test-Time Adaptation of Generative Spoken Language Models
Yuan-Kuei Wu, Yang Liu, Yiteng Huang +9
Spoken Language Models (SLMs) are increasingly central to modern speech-driven applications, but performance degrades under acoustic shift - real-world noise, reverberation, and mi…
Multi-Channel Differential ASR for Robust Wearer Speech Recognition on Smart Glasses
Yufeng Yang, Yiteng Huang, Yong Xu +9
With the growing adoption of wearable devices such as smart glasses for AI assistants, wearer speech recognition (WSR) is becoming increasingly critical to next-generation human-co…
MMW: Side Talk Rejection Multi-Microphone Whisper on Smart Glasses
Yang Liu, Li Wan, Yiteng Huang +5
Smart glasses are increasingly positioned as the next-generation interface for ubiquitous access to large language models (LLMs). Nevertheless, achieving reliable interaction in re…
Thinking in Directivity: Speech Large Language Model for Multi-Talker Directional Speech Recognition
Jiamin Xie, Ju Lin, Yiteng Huang +8
Recent studies have demonstrated that prompting large language models (LLM) with audio encodings enables effective speech recognition capabilities. However, the ability of Speech L…
MASV: Speaker Verification with Global and Local Context Mamba
Yang Liu, Li Wan, Yiteng Huang +3
Deep learning models like Convolutional Neural Networks and transformers have shown impressive capabilities in speech verification, gaining considerable attention in the research c…
M-BEST-RQ: A Multi-Channel Speech Foundation Model for Smart Glasses
Yufeng Yang, Desh Raj, Ju Lin +8
The growing popularity of multi-channel wearable devices, such as smart glasses, has led to a surge of applications such as targeted speech recognition and enhanced hearing. Howeve…
Effective Integration of KAN for Keyword Spotting
Anfeng Xu, Biqiao Zhang, Shuyu Kong +4
Keyword spotting (KWS) is an important speech processing component for smart devices with voice assistance capability. In this paper, we investigate if Kolmogorov-Arnold Networks (…
Query-by-Example Keyword Spotting Using Spectral-Temporal Graph Attentive Pooling and Multi-Task Learning
Zhenyu Wang, Shuyu Kong, Li Wan +6
Existing keyword spotting (KWS) systems primarily rely on predefined keyword phrases. However, the ability to recognize customized keywords is crucial for tailoring interactions wi…
Disentangled Training with Adversarial Examples For Robust Small-footprint Keyword Spotting
Zhenyu Wang, Li Wan, Biqiao Zhang +5
A keyword spotting (KWS) engine that is continuously running on device is exposed to various speech signals that are usually unseen before. It is a challenging problem to build a s…
AGADIR: Towards Array-Geometry Agnostic Directional Speech Recognition
Ju Lin, Niko Moritz, Yiteng Huang +4
Wearable devices like smart glasses are approaching the compute capability to seamlessly generate real-time closed captions for live conversations. We build on our recently introdu…
FADI-AEC: Fast Score Based Diffusion Model Guided by Far-end Signal for Acoustic Echo Cancellation
Yang Liu, Li Wan, Yun Li +5
Despite the potential of diffusion models in speech enhancement, their deployment in Acoustic Echo Cancellation (AEC) has been restricted. In this paper, we propose DI-AEC, pioneer…
Directional Source Separation for Robust Speech Recognition on Smart Glasses
Tiantian Feng, Ju Lin, Yiteng Huang +7
Modern smart glasses leverage advanced audio sensing and machine learning technologies to offer real-time transcribing and captioning services, considerably enriching human experie…
Handling the Alignment for Wake Word Detection: A Comparison Between Alignment-Based, Alignment-Free and Hybrid Approaches
Vinicius Ribeiro, Yiteng Huang, Yuan Shangguan +3
Wake word detection exists in most intelligent homes and portable devices. It offers these devices the ability to "wake up" when summoned at a low cost of power and computing. This…
LiCo-Net: Linearized Convolution Network for Hardware-efficient Keyword Spotting
Haichuan Yang, Zhaojun Yang, Li Wan +10
This paper proposes a hardware-efficient architecture, Linearized Convolution Network (LiCo-Net) for keyword spotting. It is optimized specifically for low-power processor units li…