Zobrazeno 1 - 10
of 19
pro vyhledávání: '"Amit Juneja"'
Publikováno v:
First Break. 40:79-84
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::fae30c97bf1f929be64937fff5af8495
https://doi.org/10.3997/1365-2397.fb2022017
https://doi.org/10.3997/1365-2397.fb2022017
Autor:
Amit Juneja, Michael M. Marefat
Publikováno v:
BHI
Stacked Denoising Autoencoders (SDA) are deep networks which have superior generative properties and therefore can be trained and retrained to learn the structure of a patient's heart beat signal with minimal training data. This approach is particula
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::18644aa144a5a1148343058dc24485a5
https://doi.org/10.1109/bhi.2019.8834566
https://doi.org/10.1109/bhi.2019.8834566
Autor:
Amit Juneja, Michael M. Marefat
Publikováno v:
EMBC
Ventricular Tachycardia (VT) is a dangerous arrhythmic event which can lead to sudden cardiac death if not detected and taken care of in time. This work uses non-linear features derived from Recurrence Quantification Analysis (RQA) along with Kolmogo
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::f758dd3f553ab3d04f73146414aecad0
https://pubmed.ncbi.nlm.nih.gov/28268386
https://pubmed.ncbi.nlm.nih.gov/28268386
Autor:
Amit Juneja
Publikováno v:
The Journal of the Acoustical Society of America. 131:EL256-EL261
The accuracy of automatic speech recognition (ASR) systems is generally evaluated using corpora of grammatically sound read speech or natural spontaneous speech. This prohibits an accurate estimation of the performance of the acoustic modeling part o
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::eb60b799318d1f48be0e90b32823620e
https://doi.org/10.1121/1.3684744
https://doi.org/10.1121/1.3684744
Autor:
Carol Y. Espy-Wilson, Amit Juneja
Publikováno v:
The Journal of the Acoustical Society of America. 123:1154-1168
A probabilistic framework for a landmark-based approach to speech recognition is presented for obtaining multiple landmark sequences in continuous speech. The landmark detection module uses as input acoustic parameters (APs) that capture the acoustic
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::ef9cc38f07662306362e7973b095bb58
https://doi.org/10.1121/1.2823754
https://doi.org/10.1121/1.2823754
Autor:
Orin Hoffman, Chris Blanco, Jeffrey Czerniak, Dongqing Liu, Amit Juneja, Lester S. H. Ngia, Tarun Pruthi, Jonathan Brown, Brian Hoffman
Publikováno v:
SPIE Proceedings.
This paper reports on a Soldier Experiment performed by the Army Research Lab's Human Research Engineering Directorate (HRED) Field Element located at the Maneuver Center of Excellence, Ft. Benning, and a Limited Use Assessment conducted by the Marin
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::4346f54c1776f448b287e800ee84e2ff
https://doi.org/10.1117/12.852507
https://doi.org/10.1117/12.852507
Autor:
Jeffrey Czerniak, Amit Juneja, Chris Blanco, Jonathan Brown, Siddharth R. Chhatpar, Dongqing Liu, Tarun Pruthi, Orin Hoffman, Robert E. Karlsen
Publikováno v:
SPIE Proceedings.
This paper reports on a Field Experiment carried out by the Human Research and Engineering Directorate at Ft. Benning to evaluate the efficacy of using speech to control an Unmanned Ground Vehicle (UGV) concurrently with a handcontroller. The SPEAR s
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::3694e73ed1f21a71a3aea2053ac880b5
https://doi.org/10.1117/12.818854
https://doi.org/10.1117/12.818854
Autor:
Dong Lin, Orin Hoffman, Amit Juneja, Chris Vlach, Siddharth R. Chhatpar, Tarun Pruthi, Tristan Lewis, Craig Birkhimer, Lester S. H. Ngia
Publikováno v:
SPIE Proceedings.
Hands-free control of unmanned ground vehicles is essential for soldiers, bomb disposal squads, and first responders. Having their hands free for other equipment and tasks allows them to be safer and more mobile. Currently, the most successful hands-
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::e2c91c3bd77f158615de9dd673857f69
https://doi.org/10.1117/12.777877
https://doi.org/10.1117/12.777877
Publikováno v:
INTERSPEECH
In this paper, we compare a Probabilistic Landmark-Based speech recognition System (LBS) which uses Knowledge-based Acoustic Parameters (APs) as the front-end with an HMMbased recognition system that uses the Mel-Frequency Cepstral Coefficients as it
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::40cbf1bd5249ce12c4b15ebb14a86c78
https://doi.org/10.21437/interspeech.2007-324
https://doi.org/10.21437/interspeech.2007-324