Jan Trmal

1.8k total citations
23 papers, 716 citations indexed

About

Jan Trmal is a scholar working on Artificial Intelligence, Signal Processing and Computer Vision and Pattern Recognition. According to data from OpenAlex, Jan Trmal has authored 23 papers receiving a total of 716 indexed citations (citations by other indexed papers that have themselves been cited), including 22 papers in Artificial Intelligence, 11 papers in Signal Processing and 2 papers in Computer Vision and Pattern Recognition. Recurrent topics in Jan Trmal's work include Speech Recognition and Synthesis (22 papers), Natural Language Processing Techniques (14 papers) and Music and Audio Processing (9 papers). Jan Trmal is often cited by papers focused on Speech Recognition and Synthesis (22 papers), Natural Language Processing Techniques (14 papers) and Music and Audio Processing (9 papers). Jan Trmal collaborates with scholars based in United States, Iran and China. Jan Trmal's co-authors include Sanjeev Khudanpur, Daniel Povey, Pegah Ghahremani, Korbinian Riedhammer, Bagher BabaAli, Guoguo Chen, David Yarowsky, Shinji Watanabe, Chunxi Liu and Wei Zou and has published in prestigious journals such as Language Resources and Evaluation and Figshare.

In The Last Decade

Jan Trmal

21 papers receiving 610 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Jan Trmal United States 10 658 411 57 53 15 23 716
Erica Cooper Japan 15 545 0.8× 410 1.0× 49 0.9× 61 1.2× 14 0.9× 58 644
Qiantong Xu Israel 7 643 1.0× 311 0.8× 46 0.8× 80 1.5× 26 1.7× 12 730
Kushal Lakhotia Israel 10 830 1.3× 456 1.1× 93 1.6× 94 1.8× 30 2.0× 11 950
Larry Gillick United States 13 605 0.9× 390 0.9× 47 0.8× 90 1.7× 12 0.8× 32 723
Nagendra Kumar Goel India 8 585 0.9× 496 1.2× 99 1.7× 43 0.8× 8 0.5× 13 663
Thomas Merritt United Kingdom 9 258 0.4× 191 0.5× 43 0.8× 35 0.7× 14 0.9× 25 328
Javier Latorre United Kingdom 13 497 0.8× 377 0.9× 71 1.2× 51 1.0× 10 0.7× 35 554
Kyu J. Han United States 12 371 0.6× 311 0.8× 50 0.9× 44 0.8× 11 0.7× 38 456
Yatharth Saraf United States 9 385 0.6× 225 0.5× 23 0.4× 57 1.1× 13 0.9× 17 459
Harald Höge Germany 11 362 0.6× 280 0.7× 51 0.9× 49 0.9× 14 0.9× 52 428

Countries citing papers authored by Jan Trmal

Since Specialization
Citations

This map shows the geographic impact of Jan Trmal'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 Jan Trmal with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jan Trmal more than expected).

Fields of papers citing papers by Jan Trmal

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Jan Trmal. 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 Jan Trmal. The network helps show where Jan Trmal may publish in the future.

Co-authorship network of co-authors of Jan Trmal

This figure shows the co-authorship network connecting the top 25 collaborators of Jan Trmal. A scholar is included among the top collaborators of Jan Trmal 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 Jan Trmal. Jan Trmal is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Huang, Ruizhe, et al.. (2023). Building Keyword Search System from End-To-End Asr Systems. 7. 1–5. 3 indexed citations
2.
Chen, Guoguo, Wei-Qiang Zhang, Chao Weng, et al.. (2021). GigaSpeech: An Evolving, Multi-Domain ASR Corpus with 10,000 Hours of Transcribed Audio. 3670–3674. 117 indexed citations
3.
Wiesner, Matthew, Mousmita Sarma, Ashish Arora, et al.. (2021). Training Hybrid Models on Noisy Transliterated Transcripts for Code-Switched Speech Recognition. 2906–2910. 3 indexed citations
4.
Wiesner, Matthew, Oliver Adams, David Yarowsky, Jan Trmal, & Sanjeev Khudanpur. (2019). Zero-Shot Pronunciation Lexicons for Cross-Language Acoustic Model Transfer. 1048–1054. 2 indexed citations
5.
Liu, Chunxi, et al.. (2019). Bottom-Up Unsupervised Word Discovery via Acoustic Units. 1–5. 1 indexed citations
6.
Liu, Chunxi, Matthew Wiesner, Shinji Watanabe, et al.. (2018). Low-Resource Contextual Topic Identification on Speech. 656–663.
7.
Švec, Ján, et al.. (2018). On the Use of Grapheme Models for Searching in Large Spoken Archives. 2016 may. 6259–6263. 2 indexed citations
8.
Wiesner, Matthew, Chunxi Liu, Craig Harman, et al.. (2018). Automatic Speech Recognition and Topic Identification from Speech for Almost-Zero-Resource Languages. 2052–2056. 4 indexed citations
9.
Hadian, Hossein, Daniel Povey, Hossein Sameti, Jan Trmal, & Sanjeev Khudanpur. (2018). Improving LF-MMI Using Unconstrained Supervisions for ASR. 88. 43–47. 4 indexed citations
10.
Richardson, Fred, Pedro A. Torres‐Carrasquillo, Douglas Sturim, et al.. (2018). The MIT Lincoln Laboratory / JHU / EPITA-LSE LRE17 System. 54–59.
11.
Trmal, Jan, Matthew Wiesner, Vijayaditya Peddinti, et al.. (2017). The Kaldi OpenKWS System: Improving Low Resource Keyword Search. 3597–3601. 22 indexed citations
12.
13.
Chodroff, Eleanor, et al.. (2016). New release of Mixer-6: Improved validity for phonetic study of speaker variation and identification. Language Resources and Evaluation. 1323–1327. 3 indexed citations
14.
Kumar, Gaurav, et al.. (2015). A Coarse-Grained Model for Optimal Coupling of ASR and SMT Systems for Speech Translation. 1902–1907. 5 indexed citations
15.
Liu, Chunxi, et al.. (2014). Low-resource open vocabulary keyword search using point process models. 2789–2793. 10 indexed citations
16.
Trmal, Jan, et al.. (2014). Improving deep neural network acoustic models using generalized maxout networks. 215–219. 183 indexed citations
17.
Trmal, Jan, Guoguo Chen, Sanjeev Khudanpur, et al.. (2014). A keyword search system using open source software. Figshare. 18. 530–535. 23 indexed citations
18.
Ghahremani, Pegah, Bagher BabaAli, Daniel Povey, et al.. (2014). A pitch extraction algorithm tuned for automatic speech recognition. 2494–2498. 196 indexed citations
19.
Chen, Guoguo, et al.. (2013). Using proxies for OOV keywords in the keyword search task. 416–421. 67 indexed citations
20.
Chen, Guoguo, et al.. (2013). Quantifying the value of pronunciation lexicons for keyword search in lowresource languages. 8560–8564. 35 indexed citations

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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