← Search

Ju Lin

7 accepted papers

2025

Directional Source Separation for Robust Speech Recognition on Smart Glasses

ICASSP 2025accepted

Modern smart glasses leverage machine learning to offer real-time transcriptions, considerably enriching human communication experiences. However, such systems frequently encounter challenges related to environmental noises, leading to decreased speech recognition. To improve voice quality, this wor…

Cited by 15SourceScholar
2025

M-BEST-RQ: A Multi-Channel Speech Foundation Model for Smart Glasses

ICASSP 2025accepted

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. However, current approaches to solve these tasks use independently trained models, which may not benefit from large amounts of…

Cited by 0SourceScholar
2024

AGADIR: Towards Array-Geometry Agnostic Directional Speech Recognition

ICASSP 2024accepted

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 introduced directional Automatic Speech Recognition (ASR) for smart glasses that have microphone arrays, which fuses multi-chan…

Cited by 0SourceScholar
2023

Egocentric Audio-Visual Noise Suppression

ICASSP 2023accepted

This paper studies audio-visual noise suppression for egocentric videos -where the speaker is not captured in the video. Instead, potential noise sources are visible on screen with the camera emulating the off-screen speaker’s view of the outside world. This setting is different from prior work in a…

Cited by 0SourceScholar
2022

Architecture for Variable Bitrate Neural Speech Codec with Configurable Computation Complexity

ICASSP 2022accepted

Low bitrate speech codecs have become an area of intense research. Traditional speech codecs, which use signal processing methods to encode and decode speech, often suffer from quality issues at low bitrates. A neural speech codec, which uses a deep neural network in the compression pipeline, can he…

Cited by 0SourceScholar
2021

A Time-Domain Convolutional Recurrent Network for Packet Loss Concealment

ICASSP 2021accepted

Packet loss may affect a wide range of applications that use voice over IP (VoIP), e.g. video conferencing. In this paper, we investigate a time-domain convolutional recurrent network (CRN) for online packet loss concealment. The CRN comprises a convolutional encoder-decoder structure and long short…

Cited by 0SourceScholar