Daniel Willett

647 total citations
40 papers, 419 citations indexed

About

Daniel Willett is a scholar working on Artificial Intelligence, Signal Processing and Computer Vision and Pattern Recognition. According to data from OpenAlex, Daniel Willett has authored 40 papers receiving a total of 419 indexed citations (citations by other indexed papers that have themselves been cited), including 35 papers in Artificial Intelligence, 26 papers in Signal Processing and 10 papers in Computer Vision and Pattern Recognition. Recurrent topics in Daniel Willett's work include Speech Recognition and Synthesis (31 papers), Speech and Audio Processing (22 papers) and Music and Audio Processing (12 papers). Daniel Willett is often cited by papers focused on Speech Recognition and Synthesis (31 papers), Speech and Audio Processing (22 papers) and Music and Audio Processing (12 papers). Daniel Willett collaborates with scholars based in Germany, Japan and United Kingdom. Daniel Willett's co-authors include Gerhard Rigoll, Joel Pinto, Shigeru Katagiri, Ralf Schlüter, Joachim Köhler, Zoltán Tüske, Martha Larson, Yulan Liu, A. Kosmala and Frank Wallhoff and has published in prestigious journals such as IEEE Transactions on Speech and Audio Processing, IEEE Transactions on Consumer Electronics and Neural Information Processing Systems.

In The Last Decade

Daniel Willett

37 papers receiving 343 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Daniel Willett Germany 13 367 209 60 26 15 40 419
Andrew Morris Switzerland 10 284 0.8× 250 1.2× 54 0.9× 20 0.8× 13 0.9× 25 384
Milind Mahajan United Kingdom 8 279 0.8× 150 0.7× 60 1.0× 11 0.4× 16 1.1× 13 323
Kari Laurila Finland 7 281 0.8× 281 1.3× 50 0.8× 18 0.7× 22 1.5× 18 366
B. Maison Belgium 11 157 0.4× 184 0.9× 134 2.2× 18 0.7× 14 0.9× 33 318
Janne Pylkkönen Finland 8 382 1.0× 112 0.5× 26 0.4× 18 0.7× 6 0.4× 15 413
Christian Plahl Germany 14 300 0.8× 212 1.0× 107 1.8× 12 0.5× 35 2.3× 21 372
Hossein Hadian Iran 8 296 0.8× 206 1.0× 30 0.5× 11 0.4× 4 0.3× 16 333
Stephan Kanthak Germany 13 439 1.2× 183 0.9× 37 0.6× 20 0.8× 4 0.3× 20 454
I. Lee Hetherington United States 11 305 0.8× 113 0.5× 27 0.5× 26 1.0× 5 0.3× 18 327
V. Valtchev United Kingdom 7 479 1.3× 347 1.7× 70 1.2× 19 0.7× 5 0.3× 9 512

Countries citing papers authored by Daniel Willett

Since Specialization
Citations

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

Fields of papers citing papers by Daniel Willett

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Daniel Willett

This figure shows the co-authorship network connecting the top 25 collaborators of Daniel Willett. A scholar is included among the top collaborators of Daniel Willett 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 Daniel Willett. Daniel Willett 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.
Weninger, Felix, et al.. (2019). Deep Learning Based Mandarin Accent Identification for Accent Robust ASR. 510–514. 25 indexed citations
2.
Zhang, Zixing, Joel Pinto, Christian Plahl, Björn W. Schuller, & Daniel Willett. (2014). Channel mapping using bidirectional long short-term memory for dereverberation in hands-free voice controlled devices. IEEE Transactions on Consumer Electronics. 60(3). 525–533. 18 indexed citations
3.
Willett, Daniel & Chuanglong He. (2008). Discriminative training for complementariness in system combination.. Conference of the International Speech Communication Association. 37(3). 919–90. 2 indexed citations
4.
Brueckner, Raymond, et al.. (2006). Language Identification In Vocal Music.. Zenodo (CERN European Organization for Nuclear Research). 377–379. 8 indexed citations
5.
Willett, Daniel, et al.. (2006). Discriminatively Trained Context-Dependent Duration-Bigram Models for Korean Digit Recognition. 1. I–25. 1 indexed citations
6.
Willett, Daniel. (2006). Context-Dependent Duration Modeling. 1. 421–424. 3 indexed citations
7.
Willett, Daniel, et al.. (2006). Experiments on Chinese speech recognition with tonal models and pitch estimation using the Mandarin speecon data. paper 1452–Tue3A2O.6. 5 indexed citations
8.
Willett, Daniel, Erik McDermott, & Shigeru Katagiri. (2005). Smoothed language model incorporation for efficient time-synchronous beam search decoding in LVCSR. 25. 178–181.
9.
Willett, Daniel, et al.. (2002). Unsupervised language model adaptation for lecture speech transcription. 1413–1416. 21 indexed citations
10.
Rigoll, Gerhard & Daniel Willett. (2002). A NN/HMM hybrid for continuous speech recognition with a discriminant nonlinear feature extraction. 1. 9–12. 5 indexed citations
11.
Willett, Daniel, et al.. (2002). Efficient search with posterior probability estimates in HMM-based speech recognition. 2. 821–824. 2 indexed citations
12.
Willett, Daniel, et al.. (2002). Improved degraded document recognition with hybrid modeling techniques and character n-grams. 4. 438–441. 6 indexed citations
13.
Wallhoff, Frank, Daniel Willett, & Gerhard Rigoll. (2001). Scaled likelihood linear regression for hidden Markov model adaptation. 1229–1232. 1 indexed citations
14.
Willett, Daniel, et al.. (1999). Experiments in topic indexing of broadcast news using neural networks. 1093–1096 vol.2. 2 indexed citations
15.
16.
Kosmala, A., Daniel Willett, & Gerhard Rigoll. (1999). Advanced state clustering for very large vocabulary HMM-based on-line handwriting recognition. 442–445. 6 indexed citations
17.
18.
Willett, Daniel, et al.. (1998). Soft state-tying for HMM-based speech recognition. paper 0346–0. 3 indexed citations
19.
Willett, Daniel, et al.. (1998). Confidence measures for HMM-based speech recognition. paper 0525–0. 22 indexed citations
20.
Willett, Daniel & Gerhard Rigoll. (1997). Hybrid NN/HMM-Based Speech Recognition with a Discriminant Neural Feature Extraction. Neural Information Processing Systems. 10. 763–769. 2 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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