Kate Knill

1.1k total citations
53 papers, 712 citations indexed

About

Kate Knill is a scholar working on Artificial Intelligence, Signal Processing and Computer Vision and Pattern Recognition. According to data from OpenAlex, Kate Knill has authored 53 papers receiving a total of 712 indexed citations (citations by other indexed papers that have themselves been cited), including 49 papers in Artificial Intelligence, 22 papers in Signal Processing and 3 papers in Computer Vision and Pattern Recognition. Recurrent topics in Kate Knill's work include Speech Recognition and Synthesis (40 papers), Natural Language Processing Techniques (24 papers) and Speech and Audio Processing (21 papers). Kate Knill is often cited by papers focused on Speech Recognition and Synthesis (40 papers), Natural Language Processing Techniques (24 papers) and Speech and Audio Processing (21 papers). Kate Knill collaborates with scholars based in United Kingdom, Japan and United States. Kate Knill's co-authors include Mark Gales, Anton Ragni, Shakti P. Rath, Philip C. Woodland, Andrey Malinin, Konstantinos G. Kyriakopoulos, K. K. Chin, Haipeng Wang, Masami Akamine and Ralf Schlüter and has published in prestigious journals such as IEEE Journal of Selected Topics in Signal Processing, Apollo (University of Cambridge) and White Rose Research Online (University of Leeds, The University of Sheffield, University of York).

In The Last Decade

Kate Knill

49 papers receiving 609 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Kate Knill United Kingdom	16	682	390	52	30	16	53	712
Ariya Rastrow United States	16	905 1.3×	562 1.4×	50 1.0×	59 2.0×	10 0.6×	54	955
Anton Ragni United Kingdom	17	688 1.0×	405 1.0×	27 0.5×	36 1.2×	11 0.7×	50	739
Jan Trmal United States	10	658 1.0×	411 1.1×	57 1.1×	53 1.8×	12 0.8×	23	716
Preethi Jyothi India	12	415 0.6×	198 0.5×	58 1.1×	65 2.2×	13 0.8×	78	484
Ching-Feng Yeh Taiwan	13	365 0.5×	227 0.6×	39 0.8×	31 1.0×	7 0.4×	28	463
Harald Höge Germany	11	362 0.5×	280 0.7×	51 1.0×	49 1.6×	12 0.8×	52	428
John Butzberger United States	12	447 0.7×	212 0.5×	43 0.8×	49 1.6×	23 1.4×	16	490
Mikel Peñagarikano Spain	13	469 0.7×	368 0.9×	26 0.5×	32 1.1×	13 0.8×	71	509
Andrej Ljolje United States	15	534 0.8×	306 0.8×	89 1.7×	76 2.5×	10 0.6×	39	605
Yuan Shangguan United States	8	481 0.7×	305 0.8×	31 0.6×	39 1.3×	12 0.8×	19	543

Countries citing papers authored by Kate Knill

Since Specialization

Citations

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

Fields of papers citing papers by Kate Knill

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Kate Knill

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

Braunschweiler, Norbert, et al.. (2024). Advancing Faithfulness of Large Language Models in Goal-Oriented Dialogue Question Answering. 1–7. 1 indexed citations

Gales, Mark, et al.. (2024). Investigating the Emergent Audio Classification Ability of ASR Foundation Models. Apollo (University of Cambridge). 4746–4760. 1 indexed citations

Knill, Kate, et al.. (2024). Muting Whisper: A Universal Acoustic Adversarial Attack on Speech Foundation Models. 7549–7565.

Gales, Mark, et al.. (2022). View-Specific Assessment of L2 Spoken English. Interspeech 2022. 4471–4475. 5 indexed citations

Gales, Mark, et al.. (2021). Analysing Bias in Spoken Language Assessment Using Concept Activation Vectors. Apollo (University of Cambridge). 7753–7757. 2 indexed citations

Wu, Xixin, Kate Knill, Mark Gales, & Andrey Malinin. (2020). Ensemble Approaches for Uncertainty in Spoken Language Assessment. Apollo (University of Cambridge). 3860–3864. 8 indexed citations

Gales, Mark, et al.. (2020). Universal Adversarial Attacks on Spoken Language Assessment Systems. Apollo (University of Cambridge). 3855–3859. 3 indexed citations

Lu, Yijuan, et al.. (2019). Impact of ASR Performance on Spoken Grammatical Error Detection. Apollo (University of Cambridge). 1876–1880. 5 indexed citations

Knill, Kate, Mark Gales, Konstantinos G. Kyriakopoulos, et al.. (2018). Impact of ASR Performance on Free Speaking Language Assessment. Apollo (University of Cambridge). 1641–1645. 16 indexed citations

10.

Malinin, Andrey, Anton Ragni, Kate Knill, & Mark Gales. (2017). Incorporating Uncertainty into Deep Learning for Spoken Language Assessment. Apollo (University of Cambridge). 45–50. 17 indexed citations

11.

Ragni, Anton, et al.. (2016). Multi-Language Neural Network Language Models. Apollo (University of Cambridge). 3042–3046. 6 indexed citations

12.

Ragni, Anton, et al.. (2016). Log-Linear System Combination Using Structured Support Vector Machines. Apollo (University of Cambridge). 1898–1902. 2 indexed citations

13.

Knill, Kate, et al.. (2015). Automatically grading learners’ English using a Gaussian process. Apollo (University of Cambridge). 7–12. 28 indexed citations

14.

Cooper, Erica, Víctor Soto, Julia Hirschberg, et al.. (2015). Improving speech recognition and keyword search for low resource languages using web data. 829–833. 26 indexed citations

15.

Ragni, Anton, Kate Knill, Shakti P. Rath, & Mark Gales. (2014). Data augmentation for low resource languages. Apollo (University of Cambridge). 810–814. 81 indexed citations

16.

Mamou, Jonathan, Jia Cui, Xiaodong Cui, et al.. (2013). System combination and score normalization for spoken term detection. 51. 8272–8276. 43 indexed citations

17.

Latorre, Javier, Vincent Wan, Mark Gales, et al.. (2012). Speech factorization for HMM-TTS based on cluster adaptive training. 971–974. 21 indexed citations

18.

Breslin, Catherine, K. K. Chin, Mark Gales, & Kate Knill. (2011). Integrated online speaker clustering and adaptation. 1085–1088. 10 indexed citations

19.

Maia, Ranniery, Heiga Zen, Kate Knill, Mark Gales, & Sabine Buchholz. (2011). Multipulse sequences for residual signal modeling. 1833–1836. 3 indexed citations

20.

Zen, Heiga, Norbert Braunschweiler, Sabine Buchholz, et al.. (2010). HMM-based polyglot speech synthesis by speaker and language adaptive training.. SSW. 186–191. 4 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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