Slim Essid

2.4k total citations
55 papers, 719 citations indexed

About

Slim Essid is a scholar working on Signal Processing, Computer Vision and Pattern Recognition and Artificial Intelligence. According to data from OpenAlex, Slim Essid has authored 55 papers receiving a total of 719 indexed citations (citations by other indexed papers that have themselves been cited), including 45 papers in Signal Processing, 21 papers in Computer Vision and Pattern Recognition and 18 papers in Artificial Intelligence. Recurrent topics in Slim Essid's work include Speech and Audio Processing (39 papers), Music and Audio Processing (30 papers) and Speech Recognition and Synthesis (15 papers). Slim Essid is often cited by papers focused on Speech and Audio Processing (39 papers), Music and Audio Processing (30 papers) and Speech Recognition and Synthesis (15 papers). Slim Essid collaborates with scholars based in France, Belgium and United Kingdom. Slim Essid's co-authors include Gaël Richard, Cyril Joder, Cédric Févotte, Romain Serizel, Gaël Richard, Olivier Cappé, Bertrand David, Olivier Gillet, Titouan Parcollet and Irina Illina and has published in prestigious journals such as IEEE Transactions on Signal Processing, IEEE Signal Processing Magazine and IEEE Transactions on Circuits and Systems for Video Technology.

In The Last Decade

Slim Essid

52 papers receiving 677 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Slim Essid France 15 534 377 178 67 45 55 719
Zekeriya TÜFEKCİ Türkiye 11 569 1.1× 248 0.7× 251 1.4× 72 1.1× 13 0.3× 34 698
Ryuichi Oka Japan 7 663 1.2× 527 1.4× 152 0.9× 109 1.6× 22 0.5× 58 824
Eric J. Humphrey United States 13 767 1.4× 446 1.2× 224 1.3× 130 1.9× 68 1.5× 25 856
Sebastian Ewert Germany 13 794 1.5× 526 1.4× 126 0.7× 121 1.8× 50 1.1× 48 846
Li-Chia Yang United States 8 367 0.7× 339 0.9× 123 0.7× 163 2.4× 22 0.5× 10 498
Eric D. Scheirer United States 12 1.2k 2.3× 924 2.5× 203 1.1× 270 4.0× 22 0.5× 21 1.4k
Nicholas J. Bryan United States 16 356 0.7× 230 0.6× 109 0.6× 97 1.4× 22 0.5× 32 479
Yuki Mitsufuji Japan 14 724 1.4× 181 0.5× 310 1.7× 66 1.0× 10 0.2× 65 836
Yi Ren China 15 425 0.8× 232 0.6× 435 2.4× 57 0.9× 12 0.3× 40 724
Roman Jarina Slovakia 11 248 0.5× 153 0.4× 146 0.8× 30 0.4× 7 0.2× 57 445

Countries citing papers authored by Slim Essid

Since Specialization
Citations

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

Fields of papers citing papers by Slim Essid

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Slim Essid

This figure shows the co-authorship network connecting the top 25 collaborators of Slim Essid. A scholar is included among the top collaborators of Slim Essid 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 Slim Essid. Slim Essid 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.
Serre, T., et al.. (2025). Contrastive Knowledge Distillation for Embedding Refinement in Personalized Speech Enhancement. SPIRE - Sciences Po Institutional REpository. 1–5. 1 indexed citations
2.
Richard, Gaël, et al.. (2025). Multiple Choice Learning for Efficient Speech Separation with Many Speakers. SPIRE - Sciences Po Institutional REpository. 1–5.
3.
Parcollet, Titouan, et al.. (2024). Speech self-supervised representations benchmarking: A case for larger probing heads. Computer Speech & Language. 89. 101695–101695. 1 indexed citations
4.
McFee, Brian, et al.. (2024). Self-Supervised Learning of Multi-Level Audio Representations for Music Segmentation. IEEE/ACM Transactions on Audio Speech and Language Processing. 32. 2141–2152.
5.
Billat, Véronique, Christian Berthomier, Slim Essid, et al.. (2024). Electroencephalography Response during an Incremental Test According to the VO2max Plateau Incidence. Applied Sciences. 14(13). 5411–5411. 1 indexed citations
6.
Serre, T., et al.. (2024). A Lightweight Dual-Stage Framework for Personalized Speech Enhancement Based on Deepfilternet2. SPIRE - Sciences Po Institutional REpository. 780–784. 1 indexed citations
7.
Fontaine, Mathieu, et al.. (2024). Online Speaker Diarization of Meetings Guided by Speech Separation. arXiv (Cornell University). 11356–11360. 1 indexed citations
8.
Roy, Subhankar, et al.. (2024). Collaborating Foundation Models for Domain Generalized Semantic Segmentation. SPIRE - Sciences Po Institutional REpository. 3108–3119. 9 indexed citations
9.
Parcollet, Titouan, et al.. (2022). Pretext Tasks Selection for Multitask Self-Supervised Audio Representation Learning. IEEE Journal of Selected Topics in Signal Processing. 16(6). 1439–1453. 10 indexed citations
10.
Clavel, Chloé, et al.. (2022). Opinions in Interactions : New Annotations of the SEMAINE Database. SPIRE - Sciences Po Institutional REpository. 1 indexed citations
11.
Parcollet, Titouan, et al.. (2022). Automatic Data Augmentation Selection and Parametrization in Contrastive Self-Supervised Speech Representation Learning. Interspeech 2022. 669–673. 4 indexed citations
12.
Essid, Slim, et al.. (2021). Neuro-Steered Music Source Separation With EEG-Based Auditory Attention Decoding And Contrastive-NMF. SPIRE - Sciences Po Institutional REpository. 25. 36–40. 3 indexed citations
13.
Serizel, Romain, et al.. (2020). DNN-based mask estimation for distributed speech enhancement in\n spatially unconstrained microphone arrays. arXiv (Cornell University). 16 indexed citations
14.
Serizel, Romain, et al.. (2020). Distributed speech separation in spatially unconstrained microphone\n arrays. arXiv (Cornell University). 3 indexed citations
15.
Clavel, Chloé, et al.. (2019). Early Detection of User Engagement Breakdown in Spontaneous Human-Humanoid Interaction. IEEE Transactions on Affective Computing. 12(3). 776–787. 17 indexed citations
16.
Essid, Slim, et al.. (2019). EEG-BASED DECODING OF AUDITORY ATTENTION TO A TARGET INSTRUMENT IN POLYPHONIC MUSIC. SPIRE - Sciences Po Institutional REpository. 2 indexed citations
17.
Garcia, Alexandre, et al.. (2019). From the Token to the Review: A Hierarchical Multimodal approach to Opinion Mining. arXiv (Cornell University). 5538–5547. 2 indexed citations
18.
Essid, Slim, et al.. (2017). Guiding Audio Source Separation by Video Object Information. SPIRE - Sciences Po Institutional REpository. 1 indexed citations
19.
Serizel, Romain, et al.. (2016). Acoustic scene classification with matrix factorization for unsupervised feature learning. SPIRE - Sciences Po Institutional REpository. 1 indexed citations
20.
Essid, Slim, et al.. (2014). Assessment of new spectral features for eeg-based emotion recognition.. SPIRE - Sciences Po Institutional REpository. 1 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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