Jing Xiao

An Iterative Polishing Framework based on Quality Aware Masked Language Model for Chinese Poetry Generation

2019 · arXiv (Cornell University)

Owing to its unique literal and aesthetical characteristics, automatic generation of Chinese poetry is still challenging in Artificial Intelligence, which can hardly be straightforwardly realized by end-to-end methods. In this paper, we propose a novel …

An Approach for Neural Machine Translation with Graph Attention Network

2020

The achievement of Neural Machine Translation (NMT) drew the attention of the professionals in recent years. The translation quality outperforms traditional methods such as Statistical Machine Translation. However, for the document-level machine translation tasks, the …

Dropout Regularization for Self-Supervised Learning of Transformer Encoder Speech Representation

2021

Predicting the altered acoustic frames is an effective way of self-supervised learning for speech representation.However, it is challenging to prevent the pretrained model from overfitting.In this paper, we proposed to introduce two dropout regularization methods …

ADKGN: An Attentive Dynamic Knowledge Graph Network for Sequential Recommendation

2021

Sequential recommendation system's goal is to predict users' next actions based on their historical behavior sequences. As we know, more recent items have a larger impact than the previous ones. Meanwhile, modeling users' current interests …

Enhancing Dual-Encoders with Question and Answer Cross-Embeddings for Answer Retrieval

2021

Dual-Encoders is a promising mechanism for answer retrieval in question answering (QA) systems. Currently most conventional Dual-Encoders learn the semantic representations of questions and answers merely through matching score. Researchers proposed to introduce the QA …

Adaptive Activation Network For Low Resource Multilingual Speech Recognition

2022 · ArXiv.org

Low resource automatic speech recognition (ASR) is a useful but thorny task, since deep learning ASR models usually need huge amounts of training data. The existing models mostly established a bottleneck (BN) layer by pre-training …

Adapitch: Adaption Multi-Speaker Text-to-Speech Conditioned on Pitch Disentangling with Untranscribed Data

2022 · arXiv (Cornell University)

In this paper, we proposed Adapitch, a multi-speaker TTS method that makes adaptation of the supervised module with untranscribed data. We design two self supervised modules to train the text encoder and mel decoder separately …