Tom Bagby

805 total citations · 1 hit paper
7 papers, 402 citations indexed

About

Tom Bagby is a scholar working on Artificial Intelligence, Signal Processing and Cancer Research. According to data from OpenAlex, Tom Bagby has authored 7 papers receiving a total of 402 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Artificial Intelligence, 6 papers in Signal Processing and 1 paper in Cancer Research. Recurrent topics in Tom Bagby's work include Speech Recognition and Synthesis (6 papers), Music and Audio Processing (5 papers) and Speech and Audio Processing (4 papers). Tom Bagby is often cited by papers focused on Speech Recognition and Synthesis (6 papers), Music and Audio Processing (5 papers) and Speech and Audio Processing (4 papers). Tom Bagby collaborates with scholars based in United States. Tom Bagby's co-authors include Khe Chai Sim, Kanishka Rao, Tara N. Sainath, Yuan Shangguan, Yonghui Wu, Rohit Prabhavalkar, Ruoming Pang, Ian McGraw, Deepti Bhatia and Raziel Álvarez and has published in prestigious journals such as ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).

In The Last Decade

Tom Bagby

7 papers receiving 354 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.

Streaming End-to-end Speech Recognition for Mobile Devices

2019 345 citations Yanzhang He, Tara N. Sainath et al. profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Tom Bagby United States	7	359	245	34	16	14	7	402
Deepti Bhatia United States	6	420 1.2×	263 1.1×	49 1.4×	17 1.1×	15 1.1×	11	481
Yuan Shangguan United States	8	481 1.3×	305 1.2×	39 1.1×	17 1.1×	16 1.1×	19	543
Vitaly Lavrukhin United States	6	312 0.9×	214 0.9×	44 1.3×	13 0.8×	7 0.5×	20	371
Zhendong Peng China	8	269 0.7×	197 0.8×	29 0.9×	11 0.7×	5 0.4×	13	326
Hainan Xu United States	10	547 1.5×	298 1.2×	46 1.4×	8 0.5×	7 0.5×	22	585
Roberto Gemello Italy	10	396 1.1×	299 1.2×	42 1.2×	10 0.6×	5 0.4×	50	455
Franco Mana Italy	10	369 1.0×	285 1.2×	40 1.2×	9 0.6×	5 0.4×	41	419
D.B. Paul United States	8	394 1.1×	247 1.0×	65 1.9×	9 0.6×	7 0.5×	12	431
Matt Shannon United Kingdom	11	317 0.9×	250 1.0×	26 0.8×	5 0.3×	5 0.4×	13	372

Countries citing papers authored by Tom Bagby

Since Specialization

Citations

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

Fields of papers citing papers by Tom Bagby

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Tom Bagby

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

All Works

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7 of 7 papers shown

1.

Stanton, Daisy, Matt Shannon, Soroosh Mariooryad, et al.. (2022). Speaker Generation. ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). 7897–7901. 11 indexed citations

2.

He, Yanzhang, Tara N. Sainath, Rohit Prabhavalkar, et al.. (2019). Streaming End-to-end Speech Recognition for Mobile Devices. 6381–6385. 345 indexed citations breakdown →

3.

Shafran, Izhak, Tom Bagby, & RJ Skerry-Ryan. (2018). Complex Evolution Recurrent Neural Networks (ceRNNs). 5854–5858. 6 indexed citations

4.

Variani, Ehsan, Tom Bagby, Kamel Lahouel, Erik McDermott, & Michiel Bacchiani. (2018). Sampled Connectionist Temporal Classification. 4959–4963. 6 indexed citations

5.

Bagby, Tom, Kanishka Rao, & Khe Chai Sim. (2018). Efficient Implementation of Recurrent Neural Network Transducer in Tensorflow. 506–512. 16 indexed citations

6.

Sim, Khe Chai, Arun Narayanan, Tom Bagby, Tara N. Sainath, & Michiel Bacchiani. (2017). Improving the efficiency of forward-backward algorithm using batched computation in TensorFlow. 6. 258–264. 6 indexed citations

7.

Variani, Ehsan, Tom Bagby, Erik McDermott, & Michiel Bacchiani. (2017). End-to-End Training of Acoustic Models for Large Vocabulary Continuous Speech Recognition with TensorFlow. 1641–1645. 12 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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