Daisy Stanton
Impact in
- Signal Processing top 1%
- Speech and Audio Processing
- Music and Audio Processing
- Artificial Intelligence top 1%
- Speech Recognition and Synthesis
- Natural Language Processing Techniques
- Topic Modeling
- Speech and dialogue systems
Papers in
-
- Speech Recognition and Synthesis 6
- Natural Language Processing Techniques 5
- Speech and dialogue systems 5
- Topic Modeling 2
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- Music and Audio Processing 2
- Speech and Audio Processing 1
- Co-authors
- RJ Skerry-Ryan (5 shared papers)Yuxuan Wang (3 shared papers)Ying Xiao (2 shared papers)Rif A. Saurous (2 shared papers)Yonghui Wu (1 shared paper)Zhifeng Chen (1 shared paper)Zongheng Yang (1 shared paper)Navdeep Jaitly (1 shared paper)
- Journals
- ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) (1 paper)International Conference on Machine Learning (1 paper)Empirical Methods in Natural Language Processing (1 paper)arXiv (Cornell University) (1 paper)
- Partner nations
- United StatesChina
In The Last Decade
Daisy Stanton
7 papers receiving 1.2k citations
Daisy Stanton's Hit Papers
Peers
Comparison fields: 5 of 69
- Signal Processing 745
- Artificial Intelligence 1.1k
- Computer Vision and Pattern Recognition 154
- Experimental and Cognitive Psychology 80
- Developmental Biology 4
Countries citing papers authored by Daisy Stanton
This map shows the geographic impact of Daisy Stanton'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 Daisy Stanton with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Daisy Stanton more than expected).
Fields of papers citing papers by Daisy Stanton
This network shows the impact of papers produced by Daisy Stanton. 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 Daisy Stanton. The network helps show where Daisy Stanton may publish in the future.
Co-authors
The 25 scholars most cited alongside Daisy Stanton, 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 | Tacotron: Towards End-to-End Speech Synthesis Hit paper breakdown → | 2017 | 1141 |
| 2 | 2018 | 83 | |
| 3 | Style Tokens: Unsupervised Style Modeling, Control and Transfer in End-to-End Speech Synthesis | 2018 | 75 |
| 4 | A Systematic Comparison of Phrase Table Pruning Techniques | 2012 | 28 |
| 5 | 2022 | 13 | |
| 6 | 2015 | 5 | |
| 7 | 2020 | 4 |
About Daisy Stanton
Daisy Stanton is a scholar working on Artificial Intelligence, Signal Processing, Insect Science, Renewable Energy, Sustainability and the Environment and Obstetrics and Gynecology, having authored 7 papers that have together received 1.3k indexed citations. Recurring topics across this work include Speech Recognition and Synthesis (6 papers), Natural Language Processing Techniques (5 papers), Speech and dialogue systems (5 papers), Music and Audio Processing (2 papers), Topic Modeling (2 papers) and Speech and Audio Processing (1 paper). The work is most often cited by research in Signal Processing (745 citations), Artificial Intelligence (1.1k citations), Computer Vision and Pattern Recognition (154 citations), Experimental and Cognitive Psychology (80 citations) and Developmental Biology (4 citations). Daisy Stanton has collaborated with scholars based in United States and China. Frequent co-authors include RJ Skerry-Ryan, Yuxuan Wang, Ying Xiao, Rif A. Saurous, Yonghui Wu, Zhifeng Chen, Zongheng Yang, Navdeep Jaitly, Ron J. Weiss and Rob Clark. Their work appears in journals such as ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), International Conference on Machine Learning, Empirical Methods in Natural Language Processing and arXiv (Cornell University).
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.