Ben Milner
- Signal Processing top 0.5%
- Speech and Audio Processing 76
- Music and Audio Processing 33
- Blind Source Separation Techniques 8
- Artificial Intelligence top 2%
- Speech Recognition and Synthesis 37
- Developmental Biology top 10%
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- Advanced Data Compression Techniques 12
- Computational Mechanics top 10%
- Advanced Adaptive Filtering Techniques 25
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- Hearing Loss and Rehabilitation 11
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- Underwater Acoustics Research 5
- Journals
- Speech Communication (5 papers)Computer Speech & Language (3 papers)IEEE Transactions on Audio Speech and Language Processing (2 papers)
- Partner nations
- United KingdomUnited StatesChina
In The Last Decade
Ben Milner
80 papers receiving 895 citations
Peers
Comparison fields: 5 of 72
- Signal Processing 875
- Artificial Intelligence 531
- Developmental Biology 32
- Computer Vision and Pattern Recognition 289
- Computational Mechanics 119
Countries citing papers authored by Ben Milner
This map shows the geographic impact of Ben Milner'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 Ben Milner with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ben Milner more than expected).
Fields of papers citing papers by Ben Milner
This network shows the impact of papers produced by Ben Milner. 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 Ben Milner. The network helps show where Ben Milner may publish in the future.
Co-authorship network
The 24 scholars most cited alongside Ben Milner, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2024 | 2 | |
| 2 | 2023 | 0 | |
| 3 | 2021 | 9 | |
| 4 | 2018 | 10 | |
| 5 | 2017 | 2 | |
| 6 | Voicing classification of visual speech using convolutional neural networks | 2015 | 3 |
| 7 | Speaker separation using visually-derived binary masks. | 2013 | 7 |
| 8 | 2013 | 1 | |
| 9 | Effective visually-derived Wiener filtering for audio-visual speech processing | 2009 | 5 |
| 10 | Comparing noise compensation methods for robust prediction of acoustic speech features from MFCC vectors in noise | 2008 | 2 |
| 11 | 2008 | 32 | |
| 12 | 2008 | 9 | |
| 13 | 2007 | 4 | |
| 14 | Maximising audio-visual speech correlation | 2007 | 8 |
| 15 | Kalman filter with linear predictor and harmonic noise models for noisy speech enhancement | 2006 | 0 |
| 16 | 2004 | 1 | |
| 17 | 1997 | 21 | |
| 18 | 1995 | 14 | |
| 19 | 1994 | 5 | |
| 20 | 1993 | 3 |
About Ben Milner
Ben Milner is a scholar working on Signal Processing, Computational Mechanics and Artificial Intelligence, having authored 84 papers that have together received 1.0k indexed citations. Recurring topics across this work include Speech and Audio Processing (76 papers), Speech Recognition and Synthesis (37 papers), Music and Audio Processing (33 papers), Advanced Adaptive Filtering Techniques (25 papers), Advanced Data Compression Techniques (12 papers), Hearing Loss and Rehabilitation (11 papers), Blind Source Separation Techniques (8 papers) and Underwater Acoustics Research (5 papers). The work is most often cited by research in Signal Processing (875 citations), Artificial Intelligence (531 citations) and Developmental Biology (32 citations). Ben Milner has collaborated with scholars based in United Kingdom, United States and China. Frequent co-authors include Saeed V. Vaseghi, Xu Shao, Ling Ma, Dan Smith, Jonathan Darch, Sarah Taylor, S. F. J. Cox, Robert Lee, Naomi Harte and Denise Risch. Their work appears in journals such as Speech Communication, Computer Speech & Language, IEEE Transactions on Audio Speech and Language Processing, The Journal of the Acoustical Society of America and IEEE/ACM 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.