Rahim Saeidi

1.7k total citations
65 papers, 1.2k citations indexed

About

Rahim Saeidi is a scholar working on Signal Processing, Artificial Intelligence and Computational Mechanics. According to data from OpenAlex, Rahim Saeidi has authored 65 papers receiving a total of 1.2k indexed citations (citations by other indexed papers that have themselves been cited), including 64 papers in Signal Processing, 55 papers in Artificial Intelligence and 11 papers in Computational Mechanics. Recurrent topics in Rahim Saeidi's work include Speech and Audio Processing (62 papers), Speech Recognition and Synthesis (55 papers) and Music and Audio Processing (33 papers). Rahim Saeidi is often cited by papers focused on Speech and Audio Processing (62 papers), Speech Recognition and Synthesis (55 papers) and Music and Audio Processing (33 papers). Rahim Saeidi collaborates with scholars based in Finland, Netherlands and United States. Rahim Saeidi's co-authors include Pejman Mowlaee, Tomi Kinnunen, David A. van Leeuwen, Paavo Alku, Yannis Stylianou, Jouni Pohjalainen, Maria Hansson-Sandsten, Rainer Martin, Taufiq Hasan and John H. L. Hansen and has published in prestigious journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, IEEE Signal Processing Letters and IEEE Transactions on Audio Speech and Language Processing.

In The Last Decade

Rahim Saeidi

65 papers receiving 1.1k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Rahim Saeidi Finland 21 1.1k 848 234 127 81 65 1.2k
Jahn Heymann Germany 17 1.5k 1.3× 1.4k 1.6× 372 1.6× 101 0.8× 102 1.3× 27 1.8k
Christophe Veaux France 13 791 0.7× 753 0.9× 107 0.5× 133 1.0× 126 1.6× 35 1.1k
Shinji Takaki Japan 16 823 0.7× 817 1.0× 111 0.5× 124 1.0× 59 0.7× 50 1.0k
Ben Milner United Kingdom 19 875 0.8× 531 0.6× 119 0.5× 289 2.3× 74 0.9× 84 1.0k
Cassia Valentini-Botinhao United Kingdom 17 941 0.9× 767 0.9× 178 0.8× 80 0.6× 251 3.1× 50 1.1k
Chanwoo Kim United States 15 757 0.7× 644 0.8× 150 0.6× 61 0.5× 71 0.9× 42 980
Xu Shao United Kingdom 8 867 0.8× 379 0.4× 154 0.7× 243 1.9× 156 1.9× 27 952
Hisashi Kawai Japan 15 640 0.6× 746 0.9× 101 0.4× 145 1.1× 81 1.0× 127 978
Hong-Goo Kang South Korea 17 734 0.7× 512 0.6× 152 0.6× 286 2.3× 96 1.2× 136 1.1k
Roland Maas Germany 15 873 0.8× 603 0.7× 301 1.3× 52 0.4× 145 1.8× 39 1.0k

Countries citing papers authored by Rahim Saeidi

Since Specialization
Citations

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

Fields of papers citing papers by Rahim Saeidi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Rahim Saeidi

This figure shows the co-authorship network connecting the top 25 collaborators of Rahim Saeidi. A scholar is included among the top collaborators of Rahim Saeidi 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 Rahim Saeidi. Rahim Saeidi 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.
Alku, Paavo & Rahim Saeidi. (2017). The Linear Predictive Modeling of Speech From Higher-Lag Autocorrelation Coefficients Applied to Noise-Robust Speaker Recognition. IEEE/ACM Transactions on Audio Speech and Language Processing. 25(8). 1606–1617. 13 indexed citations
2.
Saeidi, Rahim, et al.. (2016). Incorporating uncertainty as a Quality Measure in I-Vector Based Language Recognition. 74–80. 8 indexed citations
3.
4.
Saeidi, Rahim, et al.. (2015). Speaker recognition for speech under face cover. 1012–1016. 15 indexed citations
5.
Saeidi, Rahim, Paavo Alku, & Tom Bäckström. (2015). Feature Extraction Using Power-Law Adjusted Linear Prediction With Application to Speaker Recognition Under Severe Vocal Effort Mismatch. IEEE/ACM Transactions on Audio Speech and Language Processing. 24(1). 42–53. 21 indexed citations
6.
Saeidi, Rahim, Ramón Fernández Astudillo, & Dorothea Kolossa. (2015). Uncertain LDA: Including Observation Uncertainties in Discriminative Transforms. IEEE Transactions on Pattern Analysis and Machine Intelligence. 38(7). 1479–1488. 20 indexed citations
7.
Hurmalainen, Antti, Rahim Saeidi, & Tuomas Virtanen. (2015). Noise robust speaker recognition with convolutive sparse coding. 244–248. 9 indexed citations
8.
Mowlaee, Pejman, Rahim Saeidi, & Yannis Stylianou. (2014). INTERSPEECH 2014 Special Session: Phase Importance in Speech Processing Applications. 1623–1627. 14 indexed citations
9.
Mowlaee, Pejman & Rahim Saeidi. (2014). Time-frequency constraints for phase estimation in single-channel speech enhancement. 337–341. 19 indexed citations
10.
Mowlaee, Pejman, et al.. (2013). Phase-aware single-channel speech enhancement.. Conference of the International Speech Communication Association. 1872–1874. 2 indexed citations
11.
Kolossa, Dorothea, Steffen Zeiler, Rahim Saeidi, & Ramón Fernández Astudillo. (2013). Noise-Adaptive LDA: A New Approach for Speech Recognition Under Observation Uncertainty. IEEE Signal Processing Letters. 20(11). 1018–1021. 12 indexed citations
12.
Mowlaee, Pejman & Rahim Saeidi. (2013). On phase importance in parameter estimation in single-channel speech enhancement. Radboud Repository (Radboud University). 7462–7466. 21 indexed citations
13.
Saeidi, Rahim, et al.. (2013). Quality Measure Functions for Calibration of Speaker Recognition Systems in Various Duration Conditions. IEEE Transactions on Audio Speech and Language Processing. 21(11). 2425–2438. 50 indexed citations
14.
Hanilçi, Cemal, Tomi Kinnunen, Rahim Saeidi, et al.. (2012). Comparing spectrum estimators in speaker verification under additive noise degradation. Bursa Uludag University - AVESIS. 4769–4772. 12 indexed citations
15.
Saeidi, Rahim, Jouni Pohjalainen, Tomi Kinnunen, & Paavo Alku. (2010). Temporally Weighted Linear Prediction Features for Speaker Verification in Additive Noise. 8. 2 indexed citations
16.
Saeidi, Rahim, Pejman Mowlaee, Tomi Kinnunen, et al.. (2010). Signal-to-Signal Ratio Independent Speaker Identification for Co-channel Speech Signals. VBN Forskningsportal (Aalborg Universitet). 4565–4568. 21 indexed citations
17.
Kinnunen, Tomi, et al.. (2010). What else is new than the hamming window? robust MFCCs for speaker recognition via multitapering. 2734–2737. 26 indexed citations
18.
Hansson-Sandsten, Maria, et al.. (2010). Multitaper Estimation of Frequency-Warped Cepstra With Application to Speaker Verification. IEEE Signal Processing Letters. 17(4). 343–346. 26 indexed citations
19.
Pohjalainen, Jouni, Rahim Saeidi, Tomi Kinnunen, & Paavo Alku. (2010). Extended weighted linear prediction (XLP) analysis of speech and its application to speaker verification in adverse conditions. 1477–1480. 22 indexed citations
20.
Saeidi, Rahim, et al.. (2009). Particle Swarm Optimization for Sorted Adapted Gaussian Mixture Models. IEEE Transactions on Audio Speech and Language Processing. 17(2). 344–353. 17 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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