Ingo Siegert

755 total citations
63 papers, 309 citations indexed

About

Ingo Siegert is a scholar working on Artificial Intelligence, Experimental and Cognitive Psychology and Signal Processing. According to data from OpenAlex, Ingo Siegert has authored 63 papers receiving a total of 309 indexed citations (citations by other indexed papers that have themselves been cited), including 40 papers in Artificial Intelligence, 28 papers in Experimental and Cognitive Psychology and 15 papers in Signal Processing. Recurrent topics in Ingo Siegert's work include Emotion and Mood Recognition (25 papers), Speech and dialogue systems (19 papers) and Speech Recognition and Synthesis (17 papers). Ingo Siegert is often cited by papers focused on Emotion and Mood Recognition (25 papers), Speech and dialogue systems (19 papers) and Speech Recognition and Synthesis (17 papers). Ingo Siegert collaborates with scholars based in Germany, Switzerland and Russia. Ingo Siegert's co-authors include Andreas Wendemuth, Ronald Böck, Bogdan Vlasenko, Oliver Niebuhr, Ingmar Steiner, Bernd Möbius, Jörg Frommer, Wolfgang Minker, Dietmar Rösner and Alexey Karpov and has published in prestigious journals such as Sensors, Lecture notes in computer science and Language Resources and Evaluation.

In The Last Decade

Ingo Siegert

55 papers receiving 292 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Ingo Siegert Germany	10	168	166	95	50	36	63	309
Ronald Böck Germany	10	141 0.8×	175 1.1×	109 1.1×	57 1.1×	31 0.9×	45	300
Sathish Pammi Germany	9	215 1.3×	108 0.7×	61 0.6×	115 2.3×	21 0.6×	21	293
Kiavash Bahreini Netherlands	8	121 0.7×	124 0.7×	29 0.3×	31 0.6×	39 1.1×	16	318
Bela Usabaev Germany	5	200 1.2×	80 0.5×	142 1.5×	13 0.3×	38 1.1×	7	329
Kun-Yi Huang Taiwan	10	185 1.1×	210 1.3×	81 0.9×	65 1.3×	56 1.6×	25	420
Michiaki Yasumura Japan	7	118 0.7×	104 0.6×	96 1.0×	31 0.6×	49 1.4×	24	262
David Suendermann‐Oeft United States	10	275 1.6×	55 0.3×	66 0.7×	28 0.6×	28 0.8×	44	380
Carmén García Mateo Spain	12	311 1.9×	98 0.6×	279 2.9×	42 0.8×	27 0.8×	86	525
Laura Docío-Fernández Spain	12	243 1.4×	98 0.6×	169 1.8×	40 0.8×	28 0.8×	63	418
Ronald Müller Germany	6	188 1.1×	272 1.6×	218 2.3×	48 1.0×	30 0.8×	13	395

Countries citing papers authored by Ingo Siegert

Since Specialization

Citations

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

Fields of papers citing papers by Ingo Siegert

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Ingo Siegert

This figure shows the co-authorship network connecting the top 25 collaborators of Ingo Siegert. A scholar is included among the top collaborators of Ingo Siegert 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 Ingo Siegert. Ingo Siegert 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

Busch, M., et al.. (2025). Robot System Assistant (RoSA): evaluation of touch and speech input modalities for on-site HRI and telerobotics. Frontiers in Robotics and AI. 12. 1561188–1561188.

Siegert, Ingo, et al.. (2024). Challenges of German Speech Recognition: A Study on Multi-ethnolectal Speech Among Adolescents. 3045–3049.

Niebuhr, Oliver & Ingo Siegert. (2023). A digital “flat affect”? Popular speech compression codecs and their effects on emotional prosody. Frontiers in Communication. 8.

Stober, Sebastian, et al.. (2023). Anonymization of Stuttered Speech -- Removing Speaker Information while Preserving the Utterance. 41–45. 1 indexed citations

Niebuhr, Oliver & Ingo Siegert. (2022). "High on emotion?" How audio codecs interfere with the perceived charisma and emotional states of men and women. University of Southern Denmark Research Portal (University of Southern Denmark). 1 indexed citations

Siegert, Ingo, et al.. (2022). Künstliche Intelligenz für die Sprachanalyse in der Psychotherapie – Chancen und Risiken. PPmP - Psychotherapie · Psychosomatik · Medizinische Psychologie. 72(09/10). 395–396. 1 indexed citations

Siegert, Ingo, et al.. (2021). Admitting the addressee detection faultiness of voice assistants to improve the activation performance using a continuous learning framework. Cognitive Systems Research. 70. 65–79. 1 indexed citations

Silber‐Varod, Vered, et al.. (2021). A cross-language study of speech recognition systems for English, German, and Hebrew. 9(1). 1–15. 2 indexed citations

Siegert, Ingo. (2020). "Alexa in the wild" - Collecting Unconstrained Conversations with a Modern Voice Assistant in a Public Environment.. Language Resources and Evaluation. 615–619. 3 indexed citations

10.

Siegert, Ingo, et al.. (2020). Using Complexity-Identical Human- and Machine-Directed Utterances to Investigate Addressee Detection for Spoken Dialogue Systems. Sensors. 20(9). 2740–2740. 5 indexed citations

11.

Siegert, Ingo, et al.. (2019). Cross-Corpus Data Augmentation for Acoustic Addressee Detection. 274–283. 2 indexed citations

12.

Steiner, Ingmar, et al.. (2019). Comparing phonetic changes in computer-directed and human-directed speech. 7 indexed citations

13.

Siegert, Ingo & Andreas Wendemuth. (2017). ikannotate2 – A Tool Supporting Annotation of Emotions in Audio- Visual Data. 3 indexed citations

14.

Siegert, Ingo, et al.. (2016). Emotion Intelligibility within Codec-Compressed and Reduced Bandwidth Speech.. 1–5.

15.

Siegert, Ingo. (2015). Emotional and User-Specific Acoustic Cues for Improved Analysis of Naturalistic Interactions. KI - Künstliche Intelligenz. 30(1). 93–94. 4 indexed citations

16.

Siegert, Ingo, et al.. (2014). Application of image processing methods to filled pauses detection from spontaneous speech. 1816–1820. 5 indexed citations

17.

Rösner, Dietmar, Ingo Siegert, Stephan Günther, et al.. (2013). Analysis of significant dialog events in realistic human–computer interaction. Journal on Multimodal User Interfaces. 8(1). 75–86. 10 indexed citations

18.

Frommer, Jörg, Bernd Michaelis, Dietmar Rösner, et al.. (2012). Towards Emotion and Affect Detection in the Multimodal LAST MINUTE Corpus. Language Resources and Evaluation. 3064–3069. 9 indexed citations

19.

Siegert, Ingo, Ayoub Al-Hamadi, Andreas Wendemuth, et al.. (2012). Multimodal affect recognition in spontaneous HCI environment. 430–435. 7 indexed citations

20.

Scherer, Stefan, et al.. (2010). Developing an Expressive Speech Labeling Tool Incorporating the Temporal Characteristics of Emotion. Language Resources and Evaluation. 2 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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