John Kane

1.5k total citations · 1 hit paper
33 papers, 1.1k citations indexed

About

John Kane is a scholar working on Artificial Intelligence, Signal Processing and Experimental and Cognitive Psychology. According to data from OpenAlex, John Kane has authored 33 papers receiving a total of 1.1k indexed citations (citations by other indexed papers that have themselves been cited), including 26 papers in Artificial Intelligence, 22 papers in Signal Processing and 14 papers in Experimental and Cognitive Psychology. Recurrent topics in John Kane's work include Speech Recognition and Synthesis (26 papers), Speech and Audio Processing (20 papers) and Phonetics and Phonology Research (12 papers). John Kane is often cited by papers focused on Speech Recognition and Synthesis (26 papers), Speech and Audio Processing (20 papers) and Phonetics and Phonology Research (12 papers). John Kane collaborates with scholars based in Ireland, Belgium and United States. John Kane's co-authors include Christer Gobl, Thomas Drugman, Stefan Scherer, Tuomo Raitio, Gilles Degottex, Martti Vainio, Simon King, Paavo Alku, Antti Suni and Heng Lu and has published in prestigious journals such as IEEE Transactions on Audio Speech and Language Processing, Speech Communication and Language Resources and Evaluation.

In The Last Decade

John Kane

32 papers receiving 992 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.

COVAREP — A collaborative voice analysis repository for speech technologies

2014 429 citations Gilles Degottex, John Kane et al. profile →

Peers

John Kane

AI

ECP

SP

PHYSI

CVPR

Tuomo Raitio Finland

Christer Gobl Ireland

Vikram Ramanarayanan United States

Olov Engwall Sweden

Thomas Drugman Belgium

Shrikanth Narayanan United States

John-Paul Hosom United States

Florian Groß Germany

Florian Hönig Germany

Gilles Degottex Greece

Tuomo Raitio Finland

John Kane

1.2k ×1.7

AI

483 ×1.0

ECP

903 ×2.2

SP

239 ×1.1

PHYSI

166 ×1.2

CVPR

Citations per year, relative to John Kane John Kane (= 1×) peers Tuomo Raitio

Countries citing papers authored by John Kane

Since Specialization

Citations

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

Fields of papers citing papers by John Kane

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of John Kane

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

1.

Kane, John. (2020). The Last Seat in the House: The Story of Hanley Sound. Project Muse (Johns Hopkins University). 1 indexed citations

2.

Gorrostieta, Cristina, et al.. (2019). Gender De-Biasing in Speech Emotion Recognition. 2823–2827. 22 indexed citations

3.

Raitio, Tuomo, Heng Lu, John Kane, et al.. (2014). VOICE SOURCE MODELLING USING DEEP NEURAL NETWORKS FOR STATISTICAL PARAMETRIC SPEECH SYNTHESIS. Edinburgh Research Explorer (University of Edinburgh). 2290–2294. 27 indexed citations

4.

Degottex, Gilles, John Kane, Thomas Drugman, Tuomo Raitio, & Stefan Scherer. (2014). COVAREP — A collaborative voice analysis repository for speech technologies. 960–964. 429 indexed citations breakdown →

5.

Raitio, Tuomo, Heng Lu, John Kane, et al.. (2014). European Signal Processing Conference. 91 indexed citations

6.

Kane, John, et al.. (2014). Phonetic feature extraction for context-sensitive glottal source processing. Speech Communication. 59. 10–21. 9 indexed citations

7.

Kane, John, et al.. (2014). Analysing the prosodic characteristics of speech-chunks preceding silences in task-based interactions. 333–337. 8 indexed citations

8.

Kane, John, Stefan Scherer, Matthew P. Aylett, Louis–Philippe Morency, & Christer Gobl. (2013). Speaker and language independent voice quality classification applied to unlabelled corpora of expressive speech. 7982–7986. 14 indexed citations

9.

Drugman, Thomas, John Kane, Tuomo Raitio, & Christer Gobl. (2013). Prediction of creaky voice from contextual factors. 7967–7971. 4 indexed citations

10.

Kane, John & Christer Gobl. (2013). Wavelet Maxima Dispersion for Breathy to Tense Voice Discrimination. IEEE Transactions on Audio Speech and Language Processing. 21(6). 1170–1179. 63 indexed citations

11.

Kane, John, et al.. (2013). Using phonetic feature extraction to determine optimal speech regions for maximising the effectiveness of glottal source analysis. Trinity's Access to Research Output (TARA) (Trinity College Dublin). 29–33. 2 indexed citations

12.

Raitio, Tuomo, John Kane, Thomas Drugman, & Christer Gobl. (2013). HMM-based synthesis of creaky voice. Edinburgh Research Explorer (University of Edinburgh). 2316–2320. 13 indexed citations

13.

Scherer, Stefan, Georg Layher, John Kane, Heiko Neumann, & Nick Campbell. (2012). An audiovisual political speech analysis incorporating eye-tracking and perception data. Language Resources and Evaluation. 1114–1120. 15 indexed citations

14.

Kane, John, et al.. (2012). Exploiting time and frequency domain measures for precise voice source parameterisation. Trinity's Access to Research Output (TARA) (Trinity College Dublin). 6 indexed citations

15.

Kane, John, Thomas Drugman, & Christer Gobl. (2012). Improved automatic detection of creak. Computer Speech & Language. 27(4). 1028–1047. 41 indexed citations

16.

Székely, Éva, John Kane, Stefan Scherer, Christer Gobl, & Julie Carson-Berndsen. (2012). Detecting a targeted voice style in an audiobook using voice quality features. 4593–4596. 15 indexed citations

17.

Scherer, Stefan, John Kane, Christer Gobl, & Friedhelm Schwenker. (2012). Investigating fuzzy-input fuzzy-output support vector machines for robust voice quality classification. Computer Speech & Language. 27(1). 263–287. 51 indexed citations

18.

Drugman, Thomas, John Kane, & Christer Gobl. (2012). Resonator-based creaky voice detection. 1592–1595. 16 indexed citations

19.

Kane, John, et al.. (2011). ON THE USE OF CREAK IN HUNGARIAN SPONTANEOUS SPEECH. ICPhS. 1014–1017. 7 indexed citations

20.

Gobl, Christer, et al.. (2010). An exploration of voice source correlates of focus. Trinity's Access to Research Output (TARA) (Trinity College Dublin). 462–465. 13 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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