Jackson Liscombe

926 total citations
35 papers, 480 citations indexed

About

Jackson Liscombe is a scholar working on Artificial Intelligence, Experimental and Cognitive Psychology and Cognitive Neuroscience. According to data from OpenAlex, Jackson Liscombe has authored 35 papers receiving a total of 480 indexed citations (citations by other indexed papers that have themselves been cited), including 24 papers in Artificial Intelligence, 6 papers in Experimental and Cognitive Psychology and 3 papers in Cognitive Neuroscience. Recurrent topics in Jackson Liscombe's work include Speech and dialogue systems (22 papers), Topic Modeling (8 papers) and Natural Language Processing Techniques (8 papers). Jackson Liscombe is often cited by papers focused on Speech and dialogue systems (22 papers), Topic Modeling (8 papers) and Natural Language Processing Techniques (8 papers). Jackson Liscombe collaborates with scholars based in United States, Germany and United Kingdom. Jackson Liscombe's co-authors include Julia Hirschberg, Jennifer J. Venditti, Giuseppe Riccardi, Dilek Hakkani‐Tür, David Suendermann, Roberto Pieraccini, Keelan Evanini, Alexander Schmitt, Alexander Schmitt and Wolfgang Minker and has published in prestigious journals such as Journal of Speech Language and Hearing Research, Language Resources and Evaluation and PubMed.

In The Last Decade

Jackson Liscombe

33 papers receiving 431 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Jackson Liscombe United States	10	336	224	77	70	37	35	480
Richard Huber Germany	11	332 1.0×	255 1.1×	188 2.4×	83 1.2×	30 0.8×	24	534
Christoph Draxler Germany	10	245 0.7×	168 0.8×	120 1.6×	23 0.3×	53 1.4×	50	382
Véronique Aubergé France	12	179 0.5×	250 1.1×	127 1.6×	58 0.8×	44 1.2×	57	420
Fabio Tamburini Italy	14	401 1.2×	210 0.9×	65 0.8×	26 0.4×	55 1.5×	65	648
Uwe D. Reichel Germany	11	339 1.0×	339 1.5×	75 1.0×	29 0.4×	99 2.7×	69	554
Eva Strangert Sweden	12	250 0.7×	330 1.5×	57 0.7×	24 0.3×	117 3.2×	35	438
Hanae Koiso Japan	10	548 1.6×	196 0.9×	99 1.3×	59 0.8×	184 5.0×	22	704
Hansjörg Mixdorff Germany	13	404 1.2×	464 2.1×	178 2.3×	24 0.3×	67 1.8×	92	649
Barbara Kühnert France	10	144 0.4×	191 0.9×	26 0.3×	56 0.8×	48 1.3×	20	317
Loredana Cerrato Ireland	8	185 0.6×	179 0.8×	40 0.5×	72 1.0×	115 3.1×	34	364

Countries citing papers authored by Jackson Liscombe

Since Specialization

Citations

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

Fields of papers citing papers by Jackson Liscombe

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jackson Liscombe

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

All Works

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20 of 20 papers shown

McGarry, Andrew, Jackson Liscombe, Michael Neumann, et al.. (2025). Much More Than the Malady: The Promise of a Web-Based Digital Platform Incorporating Self-Report for Research and Clinical Care in Mild Cognitive Impairment. PubMed. 3(2). 100224–100224. 1 indexed citations

Liscombe, Jackson, et al.. (2025). Accessible Real-time Eye-gaze Tracking for Neurocognitive Health Assessment: A Multimodal Web-based Approach. 3060–3064.

Kothare, Hardik, et al.. (2024). Vocal and Facial Behavior During Affect Production in Autism Spectrum Disorder. Journal of Speech Language and Hearing Research. 68(2). 419–434. 1 indexed citations

Kothare, Hardik, Michael Neumann, Jackson Liscombe, et al.. (2024). How Consistent are Speech-Based Biomarkers in Remote Tracking of ALS Disease Progression Across Languages? A Case Study of English and Dutch. 2005–2009. 2 indexed citations

Kothare, Hardik, Michael Neumann, Jackson Liscombe, Jordan R. Green, & Vikram Ramanarayanan. (2023). Responsiveness, Sensitivity and Clinical Utility of Timing-Related Speech Biomarkers for Remote Monitoring of ALS Disease Progression. PubMed. 2023. 2323–2327. 3 indexed citations

Kothare, Hardik, W. J. Burke, Michael Neumann, et al.. (2022). Exploring Facial Metric Normalization For Within- and Between-Subject Comparisons in a Multimodal Health Monitoring Agent. 160–165. 2 indexed citations

Ramanarayanan, Vikram, Michael Neumann, Andrew Cornish, et al.. (2020). Toward Remote Patient Monitoring of Speech, Video, Cognitive and Respiratory Biomarkers Using Multimodal Dialog Technology.. Conference of the International Speech Communication Association. 492–493. 4 indexed citations

Suendermann, David, Jackson Liscombe, & Roberto Pieraccini. (2010). How to drink from a fire hose: one person can annoscribe 693 thousand utterances in one month. Annual Meeting of the Special Interest Group on Discourse and Dialogue. 257–260. 3 indexed citations

Schmitt, Alexander, et al.. (2010). WITcHCRafT: A Workbench for Intelligent exploraTion of Human ComputeR conversaTions. Language Resources and Evaluation. 1633–1637. 2 indexed citations

10.

Suendermann, David, Jackson Liscombe, & Roberto Pieraccini. (2010). Optimize the obvious: Automatic call flow generation. 5370–5373. 2 indexed citations

11.

Suendermann, David, et al.. (2009). From rule-based to statistical grammars: Continuous improvement of large-scale spoken dialog systems. 29. 4713–4716. 19 indexed citations

12.

Schmitt, Alexander, et al.. (2009). On NoMatchs, NoInputs and BargeIns. 128–131. 7 indexed citations

13.

Suendermann, David, et al.. (2009). A handsome set of metrics to measure utterance classification performance in spoken dialog systems. 349–356. 4 indexed citations

14.

Schmitt, Alexander, et al.. (2008). When calls go wrong: how to detect problematic calls based on log-files and emotions?. 463–466. 13 indexed citations

15.

Evanini, Keelan, et al.. (2008). Caller Experience: A method for evaluating dialog systems and its automatic prediction. 129–132. 16 indexed citations

16.

Liscombe, Jackson, Jennifer J. Venditti, & Julia Hirschberg. (2006). Detecting question-bearing turns in spoken tutorial dialogues. paper 1491–Mon1A3O.6. 7 indexed citations

17.

Venditti, Jennifer J., Julia Hirschberg, & Jackson Liscombe. (2006). Intonational cues to student questions in tutoring dialogs. paper 1407–Mon3A3O.3. 2 indexed citations

18.

Liscombe, Jackson. (2006). Detecting emotion in speech. 231–234. 6 indexed citations

19.

Liscombe, Jackson, Giuseppe Riccardi, & Dilek Hakkani‐Tür. (2005). Using context to improve emotion detection in spoken dialog systems. 1845–1848. 47 indexed citations

20.

Liscombe, Jackson, Giuseppe Riccardi, & Dilek Hakkani‐Tür. (2005). Using Context to Improve Emotion Detection in Spoken Dialog Systems. Columbia Academic Commons (Columbia University). 1845–1848. 66 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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