Shrikanth Narayanan

3.1k total citations · 2 hit papers
70 papers, 2.2k citations indexed

About

Shrikanth Narayanan is a scholar working on Artificial Intelligence, Signal Processing and Experimental and Cognitive Psychology. According to data from OpenAlex, Shrikanth Narayanan has authored 70 papers receiving a total of 2.2k indexed citations (citations by other indexed papers that have themselves been cited), including 37 papers in Artificial Intelligence, 33 papers in Signal Processing and 24 papers in Experimental and Cognitive Psychology. Recurrent topics in Shrikanth Narayanan's work include Speech and Audio Processing (30 papers), Speech Recognition and Synthesis (21 papers) and Music and Audio Processing (18 papers). Shrikanth Narayanan is often cited by papers focused on Speech and Audio Processing (30 papers), Speech Recognition and Synthesis (21 papers) and Music and Audio Processing (18 papers). Shrikanth Narayanan collaborates with scholars based in United States, Greece and United Kingdom. Shrikanth Narayanan's co-authors include C.‐C. Jay Kuo, Selina Chu, Abe Kazemzadeh, François Bar, Doğan Can, Hao Wang, Abeer Alwan, Sungbok Lee, Shiva Sundaram and Serdar Yıldırım and has published in prestigious journals such as SHILAP Revista de lepidopterología, The Journal of the Acoustical Society of America and Journal of Speech Language and Hearing Research.

In The Last Decade

Shrikanth Narayanan

69 papers receiving 2.0k citations

Hit Papers

align trajectories

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.

Environmental Sound Recognition With Time–Frequency Audio Features

2009 455 citations Selina Chu, Shrikanth Narayanan et al. profile →
A System for Real-time Twitter Sentiment Analysis of 2012 U.S. Presidential Election Cycle

2012 354 citations Hao Wang, Doğan Can et al. Meeting of the Association for Computational Linguistics profile →

Peers

Countries citing papers authored by Shrikanth Narayanan

Since Specialization

Citations

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

Fields of papers citing papers by Shrikanth Narayanan

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Shrikanth Narayanan

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

#	Work	Indexed citations
1	Knowledge-guided EEG Representation Learning 2024 ·PubMed ·(unknown), (unknown), Richard M. Leahy, Shrikanth Narayanan	1
2	On the Role of Visual Context in Enriching Music Representations 2023 ·(unknown), (unknown), Shrikanth Narayanan	2
3	Domain Adaptation for Sentiment Analysis Using Robust Internal Representations 2023 ·Mohammad Rostami, (unknown), Shrikanth Narayanan, Aram Galstyan	3
4	Using Emotion Embeddings to Transfer Knowledge between Emotions, Languages, and Annotation Formats 2023 ·(unknown), (unknown), (unknown), Keith Burghardt, Kristina Lerman, Shrikanth Narayanan	2
5	Mel frequency spectral domain defenses against adversarial attacks on speech recognition systems 2023 ·SHILAP Revista de lepidopterología ·(unknown), (unknown), (unknown), Shrikanth Narayanan	2
6	Design feasibility of an automated, machine-learning based feedback system for motivational interviewing. 2019 ·Psychotherapy ·Zac E. Imel, Brian T. Pace, Christina S. Soma, Michael Tanana, Tad Hirsch, James Gibson, Panayiotis Georgiou, Shrikanth Narayanan, David C. Atkins	60
7	Computational Modeling of Conversational Humor in Psychotherapy 2018 ·PubMed ·(unknown), (unknown), David C. Atkins, Shrikanth Narayanan	5
8	Detecting paralinguistic events in audio stream using context in features and probabilistic decisions 2015 ·Computer Speech & Language ·Rahul Gupta, Kartik Audhkhasi, Sungbok Lee, Shrikanth Narayanan	10
9	A System for Real-time Twitter Sentiment Analysis of 2012 U.S. Presidential Election Cycle breakdown → 2012 ·Meeting of the Association for Computational Linguistics ·Hao Wang, Doğan Can, Abe Kazemzadeh, François Bar, Shrikanth Narayanan	354
10	Recognition of Physical Activities in Overweight Hispanic Youth Using KNOWME Networks 2012 ·Journal of Physical Activity and Health ·B. Adar Emken, Ming Li, Gautam Thatte, Sang‐Won Lee, Murali Annavaram, Urbashi Mitra, Shrikanth Narayanan, Donna Spruijt‐Metz	15
11	An analysis of PCA-based vocal entrainment measures in married couples' affective spoken interactions 2011 ·Chi-Chun Lee, Athanasios Katsamanis, Matthew Black, Brian Baucom, Panayiotis Georgiou, Shrikanth Narayanan	27
12	A multimodal real-time MRI articulatory corpus for speech research 2011 ·Shrikanth Narayanan, Erik Bresch, Prasanta Ghosh, Louis Goldstein, Athanasios Katsamanis, Yoon Kim, Adam Lammert, Michael Proctor, Vikram Ramanarayanan, Yinghua Zhu	48
13	A robust harmony structure modeling scheme for classical music opus identification 2009 ·Samuel Kim, Panayiotis Georgiou, Shrikanth Narayanan	1
14	Automatic classification of question turns in spontaneous speech using lexical and prosodic evidence 2008 ·PubMed ·Sankaranarayanan Ananthakrishnan, Prasanta Ghosh, Shrikanth Narayanan	4
15	Recognition for synthesis: Automatic parameter selection for resynthesis of emotional speech from neutral speech 2008 ·Proceedings of the ... IEEE International Conference on Acoustics, Speech, and Signal Processing ·Murtaza Bulut, Sungbok Lee, Shrikanth Narayanan	7
16	Analysis of Audio Clustering using Word Descriptions 2007 ·Shiva Sundaram, Shrikanth Narayanan	5
17	Automatic acoustic synthesis of human-like laughter 2007 ·The Journal of the Acoustical Society of America ·Shiva Sundaram, Shrikanth Narayanan	30
18	Where am I? Scene Recognition for Mobile Robots using Audio Features 2006 ·Selina Chu, Shrikanth Narayanan, C.‐C. Jay Kuo, Maja Matarić	106
19	An acoustic study of emotions expressed in speech 2004 ·Serdar Yıldırım, Murtaza Bulut, Chul Min Lee, Abe Kazemzadeh, Zhigang Deng, Sungbok Lee, Shrikanth Narayanan, Carlos Busso	118
20	DARPA communicator dialog travel planning systems: the june 2000 data collection 2001 ·Marilyn Walker, John Aberdeen, Jason W Boland, Elizabeth Owen Bratt, John S. Garofolo, Lynette Hirschman, Anh D. Le, (unknown), Shrikanth Narayanan, (unknown), Bryan Pellom, Joseph Polifroni, Alexandros Potamianos, (unknown), Alexander I. Rudnicky, G. Lawrence Sanders, Stephanie Seneff, David Stallard, Steve Whittaker	73

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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