Mitchell McLaren

84 papers receiving 1.6k citations

Hit Papers

A novel scheme for speaker recognition using a phonetical...20142026201820222014100200300

Peers

Mitchell McLaren
Comparison fields: 5 of 61
  • Artificial Intelligence 1.7k
  • Signal Processing 1.6k
  • Computer Vision and Pattern Recognition 184
  • Experimental and Cognitive Psychology 94
  • Information Systems 39
Replace Petr Motlíček with:
Petr Motlíček Switzerland
Jonathan Shen United States
Tom Ko China
Gérard Chollet France
Denis Jouvet France
Sachin Kajarekar United States
Antonio Bonafonte Spain
Zhengyang Chen China
Jiangyan Yi China
Akinobu Lee Japan
Mitchell McLaren relative to Petr Motlíček Switzerland Petr Motlíček's profile →
Citations per field
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Petr Motlíček · 1×
Citations per year

Countries citing papers authored by Mitchell McLaren

Since Specialization
Citations

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

Fields of papers citing papers by Mitchell McLaren

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Mitchell McLaren

This figure shows the co-authorship network connecting the top 25 collaborators of Mitchell McLaren. A scholar is included among the top collaborators of Mitchell McLaren 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 Mitchell McLaren. Mitchell McLaren 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
#WorkIndexed citations
1 5
2
Temporarily-Aware Context Modeling Using Generative Adversarial Networks for Speech Activity Detection
7
3
Tampered Speaker Inconsistency Detection with Phonetically Aware Audio-visual Features
9
4 3
5 2
6 149
7
Open Language Interface for Voice Exploitation (OLIVE).
2
8 7
9 15
10 51
11 14
12
A novel scheme for speaker recognition using a phonetically-aware deep neural networkbreakdown →
343
13 21
14 50
15 18
16 5
17 31
18
Experiments in SVM-based Speaker Verification Using Short Utterances.
27
19 5
20 13

About Mitchell McLaren

Mitchell McLaren is a scholar working on Signal Processing, Artificial Intelligence and Computer Vision and Pattern Recognition, having authored 84 papers that have together received 1.9k indexed citations. Recurring topics across this work include Speech Recognition and Synthesis (81 papers), Speech and Audio Processing (67 papers) and Music and Audio Processing (55 papers). The work is most often cited by research in Signal Processing (1.6k citations), Artificial Intelligence (1.7k citations) and Computer Vision and Pattern Recognition (184 citations). Mitchell McLaren has collaborated with scholars based in United States, Netherlands and Australia. Frequent co-authors include Luciana Ferrer, Yun Lei, Nicolas Scheffer, David A. van Leeuwen, Aaron Lawson, Diego Castán, Martin Graciarena, Sridha Sridharan, Roy Wallace and Mohamad Hasan Bahari. Their work appears in journals such as IEEE Transactions on Information Forensics and Security, Engineering Applications of Artificial Intelligence and IEEE Transactions on Audio Speech and Language Processing.

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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