35 citations · 52 across the 13 of their papers we have counts for
13 papers
KD-MSLRT: Lightweight Sign Language Recognition Model Based on Mediapipe and 3D to 1D Knowledge Distillation
Yulong Li, Bolin Ren, Ke Hu +4
Artificial intelligence has achieved notable results in sign language recognition and translation. However, relatively few efforts have been made to significantly improve the quali…
Multilingual and Fully Non-Autoregressive ASR with Large Language Model Fusion: A Comprehensive Study
W. Ronny Huang, Cyril Allauzen, Tongzhou Chen +7
In the era of large models, the autoregressive nature of decoding often results in latency serving as a significant bottleneck. We propose a non-autoregressive LM-fused ASR system…
Improving Joint Speech-Text Representations Without Alignment
Cal Peyser, Zhong Meng, Ke Hu +5
The last year has seen astonishing progress in text-prompted image generation premised on the idea of a cross-modal representation space in which the text and image domains are rep…
Mixture-of-Expert Conformer for Streaming Multilingual ASR
Ke Hu, Bo Li, Tara N. Sainath +2
End-to-end models with large capacity have significantly improved multilingual automatic speech recognition, but their computation cost poses challenges for on-device applications.…
A Deliberation-based Joint Acoustic and Text Decoder
Sepand Mavandadi, Tara N. Sainath, Ke Hu +1
We propose a new two-pass E2E speech recognition model that improves ASR performance by training on a combination of paired data and unpaired text data. Previously, the joint acous…
Massively Multilingual Shallow Fusion with Large Language Models
Ke Hu, Tara N. Sainath, Bo Li +7
While large language models (LLM) have made impressive progress in natural language processing, it remains unclear how to utilize them in improving automatic speech recognition (AS…
Scaling Up Deliberation for Multilingual ASR
Ke Hu, Bo Li, Tara N. Sainath
Multilingual end-to-end automatic speech recognition models are attractive due to its simplicity in training and deployment. Recent work on large-scale training of such models has…
Improving Deliberation by Text-Only and Semi-Supervised Training
Ke Hu, Tara N. Sainath, Yanzhang He +4
Text-only and semi-supervised training based on audio-only data has gained popularity recently due to the wide availability of unlabeled text and speech data. In this work, we prop…
Streaming Align-Refine for Non-autoregressive Deliberation
Weiran Wang, Ke Hu, Tara N. Sainath
We propose a streaming non-autoregressive (non-AR) decoding algorithm to deliberate the hypothesis alignment of a streaming RNN-T model. Our algorithm facilitates a simple greedy d…
Optical Flux and Colour Variability of Blazars in the ZTF Survey
Vibhore Negi, Ravi Joshi, Krishan Chand +4
We investigate the temporal and colour variability of 897 blazars, comprising 455 BL Lacertae objects (BL Lacs) and 442 Flat Spectrum Radio Quasars (FSRQs), selected from the Roma-…
Realtime CNN-based Keypoint Detector with Sobel Filter and CNN-based Descriptor Trained with Keypoint Candidates
Xun Yuan, Ke Hu, Song Chen
The local feature detector and descriptor are essential in many computer vision tasks, such as SLAM and 3D reconstruction. In this paper, we introduce two separate CNNs, lightweigh…
Textual Echo Cancellation
Shaojin Ding, Ye Jia, Ke Hu +1
In this paper, we propose Textual Echo Cancellation (TEC) - a framework for cancelling the text-to-speech (TTS) playback echo from overlapping speech recordings. Such a system can…
Adversarial Training for Multilingual Acoustic Modeling
Ke Hu, Hasim Sak, Hank Liao
Multilingual training has been shown to improve acoustic modeling performance by sharing and transferring knowledge in modeling different languages. Knowledge sharing is usually ac…