The DOI matches its Crossref record; 4 of the 4 references it cites were found in a registry or an index.
Automatic speech recognition using a predictive echo state network classifier
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
A tutorial on hidden Markov models and selected applications in speech recognition
Rabiner, L. R. (1989) · Proceedings of the IEEE · doi:10.1109/5.18626 · Cited by 22,743
Harnessing Nonlinearity: Predicting Chaotic Systems and Saving Energy in Wireless Communication
Jaeger, H., & Haas, H. (2004) · Science · doi:10.1126/science.1091277 · Cited by 3,811
Cover, T. M. (1965) · IEEE Transactions on Electronic Computers · doi:10.1109/pgec.1965.264137 · Cited by 2,044
Speech recognition in noisy environments: A survey
Gong, Y. (1995) · Speech Communication · doi:10.1016/0167-6393(94)00059-j · Cited by 635
Cited by
Reservoir computing approaches to recurrent neural network training
Lukoševičius, M., & Jaeger, H. (2009) · Computer Science Review · doi:10.1016/j.cosrev.2009.03.005 · Cited by 2,956
Experimental demonstration of reservoir computing on a silicon photonics chip
Vandoorne, K., Mechet, P., Van Vaerenbergh, T., Fiers, M., Morthier, G., Verstraeten, D., Schrauwen, B., Dambre, J., & Bienstman, P. (2014) · Nature Communications · doi:10.1038/ncomms4541 · Cited by 892
FPGA based spike-time dependent encoder and reservoir design in neuromorphic computing processors
Yi, Y., Liao, Y., Wang, B., Fu, X., Shen, F., Hou, H., & Liu, L. (2016) · Microprocessors and Microsystems · doi:10.1016/j.micpro.2016.03.009 · Cited by 79
Using echo state networks for classification: A case study in Parkinson's disease diagnosis
Lacy, S. E., Smith, S. L., & Lones, M. A. (2018) · Artificial Intelligence in Medicine · doi:10.1016/j.artmed.2018.02.002 · Cited by 55
Metadata
- Authors
- Skowronski, M. D., & Harris, J. G.
- Venue
- Neural Networks
- Publisher
- Elsevier BV
- Published
- 2007-04
- Volume
- 20
- Issue
- 3
- Pages
- 414-423
- ISSN
- 0893-6080 (ISSN-L)
- OpenAlex
- W1984516841
- Cited by
- 218
- References
- 4
- FWCI
- 8.67
- Type
- journal article
- Language
- en
- Open access
- closed
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Automatic speech recognition using a predictive echo state network classifier. https://app.cochat.ai/papers/10.1016/j.neunet.2007.04.006
- The paper
- Skowronski, M. D., & Harris, J. G. (2007). Automatic speech recognition using a predictive echo state network classifier. Neural Networks. https://doi.org/10.1016/j.neunet.2007.04.006
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.