27 citations · 60 across the 30 of their papers we have counts for
23 papers · 1 filter
Dual-Form ASR: Semantics-Aware Inverse Text Normalization for Chinese Speech Recognition
Fengrun Zhang, Li Fu, Wangjin Zhou +3
Modern automatic speech recognition (ASR) scenarios require both spoken-form transcripts for faithful transcription and readable written-form transcripts with inverse text normaliz…
PAC: Pronunciation-Aware Contextualized Large Language Model-based Automatic Speech Recognition
Li Fu, Yu Xin, Sunlu Zeng +3
This paper presents a Pronunciation-Aware Contextualized (PAC) framework to address two key challenges in Large Language Model (LLM)-based Automatic Speech Recognition (ASR) system…
PAS: Data-Efficient Plug-and-Play Prompt Augmentation System
Miao Zheng, Hao Liang, Fan Yang +16
In recent years, the rise of Large Language Models (LLMs) has spurred a growing demand for plug-and-play AI systems. Among the various AI techniques, prompt engineering stands out…
Leveraging Label Information for Multimodal Emotion Recognition
Peiying Wang, Sunlu Zeng, Junqing Chen +4
Multimodal emotion recognition (MER) aims to detect the emotional status of a given expression by combining the speech and text information. Intuitively, label information should b…
AUGUST: an Automatic Generation Understudy for Synthesizing Conversational Recommendation Datasets
Yu Lu, Junwei Bao, Zichen Ma +4
High-quality data is essential for conversational recommendation systems and serves as the cornerstone of the network architecture development and training strategy design. Existin…
MoNET: Tackle State Momentum via Noise-Enhanced Training for Dialogue State Tracking
Haoning Zhang, Junwei Bao, Haipeng Sun +4
Dialogue state tracking (DST) aims to convert the dialogue history into dialogue states which consist of slot-value pairs. As condensed structural information memorizing all histor…
PLM: Probabilistically Permuted Prophet Language Modeling for Generative Pre-Training
Junwei Bao, Yifan Wang, Jiangyong Ying +4
Conventional autoregressive left-to-right (L2R) sequence generation faces two issues during decoding: limited to unidirectional target sequence modeling, and constrained on strong…
MuGER: Multi-Granularity Evidence Retrieval and Reasoning for Hybrid Question Answering
Yingyao Wang, Junwei Bao, Chaoqun Duan +3
Hybrid question answering (HQA) aims to answer questions over heterogeneous data, including tables and passages linked to table cells. The heterogeneous data can provide different…
UniRPG: Unified Discrete Reasoning over Table and Text as Program Generation
Yongwei Zhou, Junwei Bao, Chaoqun Duan +3
Question answering requiring discrete reasoning, e.g., arithmetic computing, comparison, and counting, over knowledge is a challenging task. In this paper, we propose UniRPG, a sem…
Mars: Modeling Context & State Representations with Contrastive Learning for End-to-End Task-Oriented Dialog
Haipeng Sun, Junwei Bao, Youzheng Wu +1
Traditional end-to-end task-oriented dialog systems first convert dialog context into belief state and action state before generating the system response. The system response perfo…
AutoQGS: Auto-Prompt for Low-Resource Knowledge-based Question Generation from SPARQL
Guanming Xiong, Junwei Bao, Wen Zhao +2
This study investigates the task of knowledge-based question generation (KBQG). Conventional KBQG works generated questions from fact triples in the knowledge graph, which could no…
LUNA: Learning Slot-Turn Alignment for Dialogue State Tracking
Yifan Wang, Jing Zhao, Junwei Bao +3
Dialogue state tracking (DST) aims to predict the current dialogue state given the dialogue history. Existing methods generally exploit the utterances of all dialogue turns to assi…
BORT: Back and Denoising Reconstruction for End-to-End Task-Oriented Dialog
Haipeng Sun, Junwei Bao, Youzheng Wu +1
A typical end-to-end task-oriented dialog system transfers context into dialog state, and upon which generates a response, which usually faces the problem of error propagation from…
OPERA:Operation-Pivoted Discrete Reasoning over Text
Yongwei Zhou, Junwei Bao, Chaoqun Duan +7
Machine reading comprehension (MRC) that requires discrete reasoning involving symbolic operations, e.g., addition, sorting, and counting, is a challenging task. According to this…
Fine- and Coarse-Granularity Hybrid Self-Attention for Efficient BERT
Jing Zhao, Yifan Wang, Junwei Bao +2
Transformer-based pre-trained models, such as BERT, have shown extraordinary success in achieving state-of-the-art results in many natural language processing applications. However…
The JDDC 2.0 Corpus: A Large-Scale Multimodal Multi-Turn Chinese Dialogue Dataset for E-commerce Customer Service
Nan Zhao, Haoran Li, Youzheng Wu +2
With the development of the Internet, more and more people get accustomed to online shopping. When communicating with customer service, users may express their requirements by mean…
RoR: Read-over-Read for Long Document Machine Reading Comprehension
Jing Zhao, Junwei Bao, Yifan Wang +4
Transformer-based pre-trained models, such as BERT, have achieved remarkable results on machine reading comprehension. However, due to the constraint of encoding length (e.g., 512…
CUSTOM: Aspect-Oriented Product Summarization for E-Commerce
Jiahui Liang, Junwei Bao, Yifan Wang +3
Product summarization aims to automatically generate product descriptions, which is of great commercial potential. Considering the customer preferences on different product aspects…
EviDR: Evidence-Emphasized Discrete Reasoning for Reasoning Machine Reading Comprehension
Yongwei Zhou, Junwei Bao, Haipeng Sun +5
Reasoning machine reading comprehension (R-MRC) aims to answer complex questions that require discrete reasoning based on text. To support discrete reasoning, evidence, typically t…
RevCore: Review-augmented Conversational Recommendation
Yu Lu, Junwei Bao, Yan Song +4
Existing conversational recommendation (CR) systems usually suffer from insufficient item information when conducted on short dialogue history and unfamiliar items. Incorporating e…
Conversational AI Systems for Social Good: Opportunities and Challenges
Peng Qi, Jing Huang, Youzheng Wu +2
Conversational artificial intelligence (ConvAI) systems have attracted much academic and commercial attention recently, making significant progress on both fronts. However, little…
SGG: Learning to Select, Guide, and Generate for Keyphrase Generation
Jing Zhao, Junwei Bao, Yifan Wang +3
Keyphrases, that concisely summarize the high-level topics discussed in a document, can be categorized into present keyphrase which explicitly appears in the source text, and absen…
K-PLUG: Knowledge-injected Pre-trained Language Model for Natural Language Understanding and Generation in E-Commerce
Song Xu, Haoran Li, Peng Yuan +5
Existing pre-trained language models (PLMs) have demonstrated the effectiveness of self-supervised learning for a broad range of natural language processing (NLP) tasks. However, m…