K. Ries

691 citations
11 papers · 356 · h-index 8

Impact in

    • Speech and dialogue systems
    • Natural Language Processing Techniques
    • Topic Modeling
    • Speech Recognition and Synthesis
    • Multi-Agent Systems and Negotiation
    • Music and Audio Processing
    • Speech and Audio Processing

Papers in

K. Ries

11 papers receiving 305 citations

Peers

K. Ries
Comparison fields: 5 of 50
  • Artificial Intelligence 275
  • Signal Processing 83
  • Human-Computer Interaction 16
  • Computer Vision and Pattern Recognition 46
  • Experimental and Cognitive Psychology 25
Replace Vasilis Karaiskos with:
Vasilis Karaiskos United Kingdom
Christine Pao United States
Kay Cohen
Brigitte Bigi France
Brian Langner United States
Maël Guillemot Switzerland
Kevin Lenzo United States
Charles T. Hemphill United States
Svetlana Stoyanchev United States
Dessi Puji Lestari Indonesia
K. Ries relative to Vasilis Karaiskos United Kingdom Vasilis Karaiskos's profile →
Citations per field
00.5×1.5×
Vasilis Karaiskos · 1×
Citations per year

Countries citing papers authored by K. Ries

Since Specialization
Citations

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

Fields of papers citing papers by K. Ries

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside K. Ries, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with K. Ries Line = papers co-authored together K. Ries links everyone, so they are left out of the graph.

All Works

11 of 11 papers shown
#Work
1 200296
2 200266
3 200262
4 199936
5 202128
6 200226
7 200219
8 199810
9 20026
10 20024
11 20023

About K. Ries

K. Ries is a scholar working on Artificial Intelligence, Signal Processing, General Health Professions, Philosophy and Education, having authored 11 papers that have together received 356 indexed citations. Recurring topics across this work include Speech Recognition and Synthesis (9 papers), Natural Language Processing Techniques (8 papers), Speech and dialogue systems (5 papers), Topic Modeling (2 papers), Science Education and Pedagogy (1 paper), Speech and Audio Processing (1 paper), Hermeneutics and Narrative Identity (1 paper) and Innovative Teaching and Learning Methods (1 paper). The work is most often cited by research in Artificial Intelligence (275 citations), Signal Processing (83 citations), Human-Computer Interaction (16 citations), Computer Vision and Pattern Recognition (46 citations) and Experimental and Cognitive Psychology (25 citations). K. Ries has collaborated with scholars based in United States, Germany and Netherlands. Frequent co-authors include Alex Waibel, Michael Finke, Martin Westphal, Klaus Zechner, Tanja Schultz, Thomas Schaaf, Hagen Soltau, Florian Metze, M. Bett and Thomas Kemp. Their work appears in journals such as Quality & Quantity and KITopen.

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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