Nicolas Scheffer

2.0k total citations · 1 hit paper
38 papers, 1.2k citations indexed

About

Nicolas Scheffer is a scholar working on Artificial Intelligence, Signal Processing and Computer Vision and Pattern Recognition. According to data from OpenAlex, Nicolas Scheffer has authored 38 papers receiving a total of 1.2k indexed citations (citations by other indexed papers that have themselves been cited), including 38 papers in Artificial Intelligence, 36 papers in Signal Processing and 3 papers in Computer Vision and Pattern Recognition. Recurrent topics in Nicolas Scheffer's work include Speech Recognition and Synthesis (37 papers), Speech and Audio Processing (32 papers) and Music and Audio Processing (28 papers). Nicolas Scheffer is often cited by papers focused on Speech Recognition and Synthesis (37 papers), Speech and Audio Processing (32 papers) and Music and Audio Processing (28 papers). Nicolas Scheffer collaborates with scholars based in United States, France and United Kingdom. Nicolas Scheffer's co-authors include Luciana Ferrer, Yun Lei, Mitchell McLaren, Martin Graciarena, Lukáš Burget, Jean-François Bonastre, Driss Matrouf, Benoît Fauve, Elizabeth Shriberg and Andreas Stolcke and has published in prestigious journals such as IEEE Transactions on Audio Speech and Language Processing, IEEE/ACM Transactions on Audio Speech and Language Processing and NTCIR.

In The Last Decade

Nicolas Scheffer

38 papers receiving 1.0k citations

Hit Papers

A novel scheme for speaker recognition using a phonetical... 2014 2026 2018 2022 2014 100 200 300
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. A novel scheme for speaker recognition using a phonetically-aware deep neural network
    2014 343 citations Yun Lei, Nicolas Scheffer et al. profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Nicolas Scheffer United States 18 1.1k 1.0k 63 37 22 38 1.2k
Petr Schwarz Czechia 16 1.3k 1.2× 1.1k 1.1× 112 1.8× 72 1.9× 15 0.7× 27 1.4k
Ariya Rastrow United States 16 905 0.8× 562 0.5× 59 0.9× 50 1.4× 10 0.5× 54 955
Oldřich Plchot Czechia 22 1.5k 1.3× 1.3k 1.2× 74 1.2× 37 1.0× 9 0.4× 69 1.6k
Jason Pelecanos United States 12 833 0.8× 836 0.8× 57 0.9× 27 0.7× 11 0.5× 43 929
Yuya Unno United States 4 789 0.7× 543 0.5× 65 1.0× 43 1.2× 8 0.4× 5 863
Jenthe Thienpondt Belgium 6 792 0.7× 704 0.7× 75 1.2× 42 1.1× 11 0.5× 13 894
Mazin G. Rahim United States 13 656 0.6× 439 0.4× 96 1.5× 52 1.4× 17 0.8× 51 734
Kishore Prahallad India 13 735 0.7× 556 0.5× 74 1.2× 88 2.4× 15 0.7× 54 811
Téva Merlin France 7 573 0.5× 548 0.5× 118 1.9× 26 0.7× 42 1.9× 16 706
Adithya Renduchintala United States 6 855 0.8× 544 0.5× 89 1.4× 45 1.2× 10 0.5× 17 934

Countries citing papers authored by Nicolas Scheffer

Since Specialization
Citations

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

Fields of papers citing papers by Nicolas Scheffer

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Nicolas Scheffer

This figure shows the co-authorship network connecting the top 25 collaborators of Nicolas Scheffer. A scholar is included among the top collaborators of Nicolas Scheffer 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 Nicolas Scheffer. Nicolas Scheffer 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.
Ferrer, Luciana, Yun Lei, Mitchell McLaren, & Nicolas Scheffer. (2015). Study of Senone-Based Deep Neural Network Approaches for Spoken Language Recognition. IEEE/ACM Transactions on Audio Speech and Language Processing. 24(1). 105–116. 51 indexed citations
2.
Scheffer, Nicolas & Yun Lei. (2014). Content matching for short duration speaker recognition. 1317–1321. 14 indexed citations
3.
Ferrer, Luciana, Yun Lei, Mitchell McLaren, & Nicolas Scheffer. (2014). Spoken language recognition based on senone posteriors. 2150–2154. 14 indexed citations
4.
Lei, Yun, Nicolas Scheffer, Luciana Ferrer, & Mitchell McLaren. (2014). A novel scheme for speaker recognition using a phonetically-aware deep neural network. 1695–1699. 343 indexed citations breakdown →
5.
Lei, Yun, Luciana Ferrer, Mitchell McLaren, & Nicolas Scheffer. (2014). A deep neural network speaker verification system targeting microphone speech. 681–685. 9 indexed citations
6.
Lei, Yun, Luciana Ferrer, Aaron Lawson, Mitchell McLaren, & Nicolas Scheffer. (2014). Application of Convolutional Neural Networks to Language Identification in Noisy Conditions. 39 indexed citations
7.
McLaren, Mitchell, Yun Lei, Nicolas Scheffer, & Luciana Ferrer. (2014). Application of convolutional neural networks to speaker recognition in noisy conditions. 52 indexed citations
8.
McLaren, Mitchell, Nicolas Scheffer, Luciana Ferrer, & Yun Lei. (2014). Effective use of DCTS for contextualizing features for speaker recognition. 2004. 4027–4031. 11 indexed citations
9.
Mitra, Vikramjit, Mitchell McLaren, Horacio Franco, Martin Graciarena, & Nicolas Scheffer. (2013). Modulation features for noise robust speaker identification. 3703–3707. 21 indexed citations
10.
Zhao, Bing, et al.. (2013). SRI's Submissions to Chinese-English PatentMT NTCIR10 Evaluation.. NTCIR. 1 indexed citations
11.
McLaren, Mitchell, Aaron Lawson, Yun Lei, & Nicolas Scheffer. (2013). Adaptive Gaussian backend for robust language identification. 84–88. 7 indexed citations
12.
Lei, Yun, Lukáš Burget, & Nicolas Scheffer. (2013). A noise robust i-vector extractor using vector taylor series for speaker recognition. 16. 6788–6791. 57 indexed citations
13.
Graciarena, Martin, Abeer Alwan, Dan Ellis, et al.. (2013). All for one: feature combination for highly channel-degraded speech activity detection. 709–713. 31 indexed citations
14.
Ferrer, Luciana, Lukáš Burget, Oldřich Plchot, & Nicolas Scheffer. (2012). A unified approach for audio characterization and its application to speaker recognition.. 317–323. 17 indexed citations
15.
Lei, Yun, Lukáš Burget, Luciana Ferrer, Martin Graciarena, & Nicolas Scheffer. (2012). Towards noise-robust speaker recognition using probabilistic linear discriminant analysis. 4253–4256. 70 indexed citations
16.
Scheffer, Nicolas, Luciana Ferrer, Martin Graciarena, et al.. (2011). The SRI NIST 2010 speaker recognition evaluation system. 5292–5295. 27 indexed citations
17.
Stolcke, Andreas, Murat Akbacak, Luciana Ferrer, et al.. (2010). Improving Language Recognition with Multilingual Phone Recognition and Speaker Adaptation Transforms.. 43. 14 indexed citations
18.
Vogt, Robbie, Jason Pelecanos, Nicolas Scheffer, Sachin Kajarekar, & Sridha Sridharan. (2009). Within-session variability modelling for factor analysis speaker verification. 1563–1566. 9 indexed citations
19.
Kajarekar, Sachin, Nicolas Scheffer, Martin Graciarena, et al.. (2009). THE SRI NIST 2008 speaker recognition evaluation system. 4205–4208. 34 indexed citations
20.
Shriberg, Elizabeth, Luciana Ferrer, Sachin Kajarekar, et al.. (2008). Detecting nonnative speech using speaker recognition approaches.. 26. 16 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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