Search Results for author: Hong Qu

Found 8 papers, 1 papers with code

Self-Annotated Training for Controllable Image Captioning

no code implementations16 Oct 2021 Zhangzi Zhu, Tianlei Wang, Hong Qu

In this paper, we propose a novel reinforcement training method for structure-related control signals: Self-Annotated Training (SAT), to improve both the accuracy and controllability of CIC models.

Image Captioning TAG

A Dual-Perception Graph Neural Network with Multi-hop Graph Generator

no code implementations15 Oct 2021 Li Zhou, Wenyu Chen, Dingyi Zeng, Shaohuan Cheng, Wanlong Liu, Hong Qu

In DPGNN, we utilize node features to construct a feature graph, and perform node representations learning based on the original topology graph and the constructed feature graph simultaneously, which conduce to capture the structural neighborhood information and the feature-related information.

Generating Human Readable Transcript for Automatic Speech Recognition with Pre-trained Language Model

no code implementations22 Feb 2021 Junwei Liao, Yu Shi, Ming Gong, Linjun Shou, Sefik Eskimez, Liyang Lu, Hong Qu, Michael Zeng

Many downstream tasks and human readers rely on the output of the ASR system; therefore, errors introduced by the speaker and ASR system alike will be propagated to the next task in the pipeline.

Data Augmentation Speech Recognition

Improving Zero-shot Neural Machine Translation on Language-specific Encoders-Decoders

no code implementations12 Feb 2021 Junwei Liao, Yu Shi, Ming Gong, Linjun Shou, Hong Qu, Michael Zeng

However, the performance of using multiple encoders and decoders on zero-shot translation still lags behind universal NMT.

Denoising Machine Translation +1

Macroscopic Control of Text Generation for Image Captioning

no code implementations20 Jan 2021 Zhangzi Zhu, Tianlei Wang, Hong Qu

With such a control signal, the controllability and diversity of existing captioning models are enhanced.

Image Captioning Text Generation +1

Improving Readability for Automatic Speech Recognition Transcription

no code implementations9 Apr 2020 Junwei Liao, Sefik Emre Eskimez, Liyang Lu, Yu Shi, Ming Gong, Linjun Shou, Hong Qu, Michael Zeng

In this work, we propose a novel NLP task called ASR post-processing for readability (APR) that aims to transform the noisy ASR output into a readable text for humans and downstream tasks while maintaining the semantic meaning of the speaker.

Grammatical Error Correction Speech Recognition

Rectified Linear Postsynaptic Potential Function for Backpropagation in Deep Spiking Neural Networks

no code implementations26 Mar 2020 Malu Zhang, Jiadong Wang, Burin Amornpaisannon, Zhixuan Zhang, VPK Miriyala, Ammar Belatreche, Hong Qu, Jibin Wu, Yansong Chua, Trevor E. Carlson, Haizhou Li

In STDBP algorithm, the timing of individual spikes is used to convey information (temporal coding), and learning (back-propagation) is performed based on spike timing in an event-driven manner.

Decision Making

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