Search Results for author: Jian Luan

Found 14 papers, 3 papers with code

BIT-Xiaomi’s System for AutoSimTrans 2022

no code implementations NAACL (AutoSimTrans) 2022 Mengge Liu, Xiang Li, Bao Chen, Yanzhi Tian, Tianwei Lan, Silin Li, Yuhang Guo, Jian Luan, Bin Wang

This system paper describes the BIT-Xiaomi simultaneous translation system for Autosimtrans 2022 simultaneous translation challenge.

Chunking Data Augmentation +1

CBSiMT: Mitigating Hallucination in Simultaneous Machine Translation with Weighted Prefix-to-Prefix Training

no code implementations7 Nov 2023 Mengge Liu, Wen Zhang, Xiang Li, Yanzhi Tian, Yuhang Guo, Jian Luan, Bin Wang, Shuoying Chen

Simultaneous machine translation (SiMT) is a challenging task that requires starting translation before the full source sentence is available.

Machine Translation Translation

From Indeterminacy to Determinacy: Augmenting Logical Reasoning Capabilities with Large Language Models

no code implementations28 Oct 2023 Hongda Sun, Weikai Xu, Wei Liu, Jian Luan, Bin Wang, Shuo Shang, Ji-Rong Wen, Rui Yan

To address these challenges, we propose DetermLR, a novel reasoning framework that formulates the reasoning process as a transformational journey from indeterminate premises to determinate ones.

Logical Reasoning

CMATH: Can Your Language Model Pass Chinese Elementary School Math Test?

no code implementations29 Jun 2023 Tianwen Wei, Jian Luan, Wei Liu, Shuang Dong, Bin Wang

We present the Chinese Elementary School Math Word Problems (CMATH) dataset, comprising 1. 7k elementary school-level math word problems with detailed annotations, source from actual Chinese workbooks and exams.

Language Modelling Math +2

UniMC: A Unified Framework for Long-Term Memory Conversation via Relevance Representation Learning

no code implementations18 Jun 2023 Kang Zhao, Wei Liu, Jian Luan, Minglei Gao, Li Qian, Hanlin Teng, Bin Wang

In this paper, we propose a Unified framework for Long-term Memory Conversations (UniMC), which increases the connection between different stages by learning relevance representation.

Representation Learning Retrieval

Exploring Better Text Image Translation with Multimodal Codebook

1 code implementation27 May 2023 Zhibin Lan, Jiawei Yu, Xiang Li, Wen Zhang, Jian Luan, Bin Wang, Degen Huang, Jinsong Su

Text image translation (TIT) aims to translate the source texts embedded in the image to target translations, which has a wide range of applications and thus has important research value.

Machine Translation Optical Character Recognition +2

Rethinking the Reasonability of the Test Set for Simultaneous Machine Translation

1 code implementation2 Mar 2023 Mengge Liu, Wen Zhang, Xiang Li, Jian Luan, Bin Wang, Yuhang Guo, Shuoying Chen

Simultaneous machine translation (SimulMT) models start translation before the end of the source sentence, making the translation monotonically aligned with the source sentence.

Machine Translation Test +1

BERT-ERC: Fine-tuning BERT is Enough for Emotion Recognition in Conversation

no code implementations17 Jan 2023 Xiangyu Qin, Zhiyu Wu, Jinshi Cui, Tingting Zhang, Yanran Li, Jian Luan, Bin Wang, Li Wang

Accordingly, we propose a novel paradigm, i. e., exploring contextual information and dialogue structure information in the fine-tuning step, and adapting the PLM to the ERC task in terms of input text, classification structure, and training strategy.

Emotion Recognition in Conversation text-classification +1

Improve Bilingual TTS Using Dynamic Language and Phonology Embedding

no code implementations7 Dec 2022 Fengyu Yang, Jian Luan, Yujun Wang

We introduce phonology embedding to capture the English differences between different phonology.

PAMA-TTS: Progression-Aware Monotonic Attention for Stable Seq2Seq TTS With Accurate Phoneme Duration Control

no code implementations9 Oct 2021 Yunchao He, Jian Luan, Yujun Wang

Sequence expansion between encoder and decoder is a critical challenge in sequence-to-sequence TTS.

HiFiSinger: Towards High-Fidelity Neural Singing Voice Synthesis

1 code implementation3 Sep 2020 Jiawei Chen, Xu Tan, Jian Luan, Tao Qin, Tie-Yan Liu

To tackle the difficulty of singing modeling caused by high sampling rate (wider frequency band and longer waveform), we introduce multi-scale adversarial training in both the acoustic model and vocoder to improve singing modeling.

Singing Voice Synthesis Vocal Bursts Intensity Prediction

DeepSinger: Singing Voice Synthesis with Data Mined From the Web

no code implementations9 Jul 2020 Yi Ren, Xu Tan, Tao Qin, Jian Luan, Zhou Zhao, Tie-Yan Liu

DeepSinger has several advantages over previous SVS systems: 1) to the best of our knowledge, it is the first SVS system that directly mines training data from music websites, 2) the lyrics-to-singing alignment model further avoids any human efforts for alignment labeling and greatly reduces labeling cost, 3) the singing model based on a feed-forward Transformer is simple and efficient, by removing the complicated acoustic feature modeling in parametric synthesis and leveraging a reference encoder to capture the timbre of a singer from noisy singing data, and 4) it can synthesize singing voices in multiple languages and multiple singers.

Singing Voice Synthesis

Adversarially Trained Multi-Singer Sequence-To-Sequence Singing Synthesizer

no code implementations18 Jun 2020 Jie Wu, Jian Luan

This paper presents a high quality singing synthesizer that is able to model a voice with limited available recordings.

XiaoiceSing: A High-Quality and Integrated Singing Voice Synthesis System

no code implementations11 Jun 2020 Peiling Lu, Jie Wu, Jian Luan, Xu Tan, Li Zhou

This paper presents XiaoiceSing, a high-quality singing voice synthesis system which employs an integrated network for spectrum, F0 and duration modeling.

Singing Voice Synthesis Vocal Bursts Intensity Prediction

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