Search Results for author: Ning Ma

Found 16 papers, 5 papers with code

SNuC: The Sheffield Numbers Spoken Language Corpus

no code implementations LREC 2022 Emma Barker, Jon Barker, Robert Gaizauskas, Ning Ma, Monica Lestari Paramita

We present SNuC, the first published corpus of spoken alphanumeric identifiers of the sort typically used as serial and part numbers in the manufacturing sector.

Partition Speeds Up Learning Implicit Neural Representations Based on Exponential-Increase Hypothesis

1 code implementation ICCV 2023 Ke Liu, Feng Liu, Haishuai Wang, Ning Ma, Jiajun Bu, Bo Han

Based on this fact, we introduce a simple partition mechanism to boost the performance of two INR methods for image reconstruction: one for learning INRs, and the other for learning-to-learn INRs.

Image Reconstruction Semantic Segmentation

Intelligibility prediction with a pretrained noise-robust automatic speech recognition model

no code implementations20 Oct 2023 Zehai Tu, Ning Ma, Jon Barker

This paper describes two intelligibility prediction systems derived from a pretrained noise-robust automatic speech recognition (ASR) model for the second Clarity Prediction Challenge (CPC2).

Automatic Speech Recognition Automatic Speech Recognition (ASR) +1

Homophily-enhanced Structure Learning for Graph Clustering

1 code implementation10 Aug 2023 Ming Gu, Gaoming Yang, Sheng Zhou, Ning Ma, Jiawei Chen, Qiaoyu Tan, Meihan Liu, Jiajun Bu

Graph clustering is a fundamental task in graph analysis, and recent advances in utilizing graph neural networks (GNNs) have shown impressive results.

Clustering Graph Clustering +1

Multi-source adversarial transfer learning for ultrasound image segmentation with limited similarity

no code implementations30 May 2023 Yifu Zhang, Hongru Li, Tao Yang, Rui Tao, Zhengyuan Liu, Shimeng Shi, Jiansong Zhang, Ning Ma, Wujin Feng, Zhanhu Zhang, Xinyu Zhang

Transfer learning provides the possibility to solve this problem, but there are too many features in natural images that are not related to the target domain.

Image Segmentation Lesion Segmentation +2

Unsupervised Uncertainty Measures of Automatic Speech Recognition for Non-intrusive Speech Intelligibility Prediction

1 code implementation8 Apr 2022 Zehai Tu, Ning Ma, Jon Barker

Non-intrusive intelligibility prediction is important for its application in realistic scenarios, where a clean reference signal is difficult to access.

Automatic Speech Recognition Automatic Speech Recognition (ASR) +1

Exploiting Hidden Representations from a DNN-based Speech Recogniser for Speech Intelligibility Prediction in Hearing-impaired Listeners

1 code implementation8 Apr 2022 Zehai Tu, Ning Ma, Jon Barker

An accurate objective speech intelligibility prediction algorithms is of great interest for many applications such as speech enhancement for hearing aids.

Speech Enhancement speech-recognition +1

Semi-Supervised Hypothesis Transfer for Source-Free Domain Adaptation

no code implementations14 Jul 2021 Ning Ma, Jiajun Bu, Lixian Lu, Jun Wen, Zhen Zhang, Sheng Zhou, Xifeng Yan

Domain Adaptation has been widely used to deal with the distribution shift in vision, language, multimedia etc.

Source-Free Domain Adaptation

Uncertainty-Guided Mixup for Semi-Supervised Domain Adaptation without Source Data

no code implementations14 Jul 2021 Ning Ma, Jiajun Bu, Zhen Zhang, Sheng Zhou

Present domain adaptation methods usually perform explicit representation alignment by simultaneously accessing the source data and target data.

Privacy Preserving Semi-supervised Domain Adaptation +1

DHASP: Differentiable Hearing Aid Speech Processing

no code implementations15 Mar 2021 Zehai Tu, Ning Ma, Jon Barker

In this paper, we explore an alternative approach to finding the optimal fitting by introducing a hearing aid speech processing framework, in which the fitting is optimised in an automated way using an intelligibility objective function based on the HASPI physiological auditory model.

Accelerating Generalized Benders Decomposition for Wireless Resource Allocation

1 code implementation3 Mar 2020 Mengyuan Lee, Ning Ma, Guanding Yu, Huaiyu Dai

Only useful cuts are added to the master problem and thus the complexity of the master problem is reduced.

An End-to-End Solution for Effectively Demoting Watermarked Images in Image Search

no code implementations28 Jan 2019 Ning Ma, Xin Zhao, Mark Bolin

We demonstrate that using these watermark signals together with the new metric in image search ranker can significantly demote the watermarked images during the online image ranking.

Image Retrieval

An Universal Image Attractiveness Ranking Framework

no code implementations12 Apr 2018 Ning Ma, Alexey Volkov, Aleksandr Livshits, Pawel Pietrusinski, Houdong Hu, Mark Bolin

We propose a new framework to rank image attractiveness using a novel pairwise deep network trained with a large set of side-by-side multi-labeled image pairs from a web image index.

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