Xingyu Na

1.9k total citations · 2 hit papers
12 papers, 968 citations indexed

About

Xingyu Na is a scholar working on Artificial Intelligence, Signal Processing and Computer Vision and Pattern Recognition. According to data from OpenAlex, Xingyu Na has authored 12 papers receiving a total of 968 indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Artificial Intelligence, 9 papers in Signal Processing and 2 papers in Computer Vision and Pattern Recognition. Recurrent topics in Xingyu Na's work include Speech Recognition and Synthesis (11 papers), Speech and Audio Processing (6 papers) and Music and Audio Processing (5 papers). Xingyu Na is often cited by papers focused on Speech Recognition and Synthesis (11 papers), Speech and Audio Processing (6 papers) and Music and Audio Processing (5 papers). Xingyu Na collaborates with scholars based in China, Switzerland and United States. Xingyu Na's co-authors include Hui Bu, Hao Zheng, Vijayaditya Peddinti, Pegah Ghahremani, Sanjeev Khudanpur, Yiming Wang, Vimal Manohar, Daniel Gálvez, Daniel Povey and Yajie Miao and has published in prestigious journals such as IEEE/ACM Transactions on Audio Speech and Language Processing, Chinese Journal of Electronics and Infoscience (Ecole Polytechnique Fédérale de Lausanne).

In The Last Decade

Xingyu Na

11 papers receiving 868 citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Purely Sequence-Trained Neural Networks for ASR Based on Lattice-Free MMI

2016 458 citations Daniel Povey, Vijayaditya Peddinti et al. profile →
AISHELL-1: An open-source Mandarin speech corpus and a speech recognition baseline

2017 431 citations Hui Bu, Xingyu Na et al. profile →

Peers

Countries citing papers authored by Xingyu Na

Since Specialization

Citations

This map shows the geographic impact of Xingyu Na's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Xingyu Na with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Xingyu Na more than expected).

Fields of papers citing papers by Xingyu Na

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Xingyu Na. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Xingyu Na. The network helps show where Xingyu Na may publish in the future.

Co-authorship network of co-authors of Xingyu Na

This figure shows the co-authorship network connecting the top 25 collaborators of Xingyu Na. A scholar is included among the top collaborators of Xingyu Na based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Xingyu Na. Xingyu Na is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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12 of 12 papers shown

#	Work	Indexed citations
1	Contextualization of ASR with LLM using phonetic retrieval-based augmentation 2025 ·Zhihong Lei, Xingyu Na, Mingbin Xu, (unknown), C Gysel, (unknown), (unknown), Zhen Huang	0
2	Enhancing CTC-based speech recognition with diverse modeling units 2024 ·(unknown), Mingbin Xu, Zhihong Lei, Zhen Huang, Xingyu Na	1
3	AISHELL-1: An open-source Mandarin speech corpus and a speech recognition baseline breakdown → 2017 ·Hui Bu, (unknown), Xingyu Na, (unknown), Hao Zheng	431
4	Handling OOVWords in Mandarin Spoken Term Detection with an Hierarchical n‐Gram Language Model 2017 ·Chinese Journal of Electronics ·(unknown), Pengyuan Zhang, Xingyu Na, (unknown), Yonghong Yan	2
5	Purely Sequence-Trained Neural Networks for ASR Based on Lattice-Free MMI breakdown → 2016 ·Daniel Povey, Vijayaditya Peddinti, Daniel Gálvez, Pegah Ghahremani, Vimal Manohar, Xingyu Na, Yiming Wang, Sanjeev Khudanpur	458
6	An empirical exploration of CTC acoustic models 2016 ·Yajie Miao, (unknown), Xingyu Na, Tom Ko, Florian Metze, Alexander Waibel	52
7	Incremental Syllable-Context Phonetic Vocoding 2015 ·IEEE/ACM Transactions on Audio Speech and Language Processing ·Miloš Cerňak, Philip N. Garner, Alexandros Lazaridis, Petr Motlíček, Xingyu Na	6
8	Improving voice quality of HMM-based speech synthesis using voice conversion method 2014 ·(unknown), (unknown), Xingyu Na, Ming Tu	3
9	Low latency parameter generation for real-time speech synthesis system 2014 ·Xingyu Na, (unknown), Jingming Kuang	2
10	Computational Auditory Scene Analysis Based Voice Activity Detection 2014 ·Ming Tu, Xiang Xie, Xingyu Na	4
11	Convolutional Pitch Target Approximation Model for Speech Synthesis 2013 ·Infoscience (Ecole Polytechnique Fédérale de Lausanne) ·Xingyu Na, Philip N. Garner	1
12	Syllable-based pitch encoding for low bit rate speech coding with recognition/synthesis architecture 2013 ·Infoscience (Ecole Polytechnique Fédérale de Lausanne) ·Miloš Cerňak, Xingyu Na, Philip N. Garner	8

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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