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Kemal Sonmez

Researcher at Oregon Health & Science University

Publications -  49
Citations -  1722

Kemal Sonmez is an academic researcher from Oregon Health & Science University. The author has contributed to research in topics: Retinopathy of prematurity & Speaker recognition. The author has an hindex of 20, co-authored 47 publications receiving 1485 citations. Previous affiliations of Kemal Sonmez include Oregon National Primate Research Center & University of Portland.

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Journal ArticleDOI

Gibbon genome and the fast karyotype evolution of small apes

Lucia Carbone, +99 more
- 11 Sep 2014 - 
TL;DR: The assembly and analysis of a northern white-cheeked gibbon genome is presented and the propensity for a gibbon-specific retrotransposon (LAVA) to insert into chromosome segregation genes and alter transcription by providing a premature termination site is described, suggesting a possible molecular mechanism for the genome plasticity of the gibbon lineage.
Proceedings ArticleDOI

Landmark-based speech recognition: report of the 2004 Johns Hopkins summer workshop

TL;DR: Three research prototype speech recognition systems are described, all of which use recently developed methods from artificial intelligence (specifically support vector machines (SVM); dynamic Bayesian networks, and maximum entropy classification) in order to implement, in the form of an ASR, current theories of human speech perception and phonology.
Journal ArticleDOI

Combining standard and throat microphones for robust speech recognition

TL;DR: In continuous-speech recognition experiments using SRI International's DECIPHER recognition system, both using artificially added noise and using recorded noisy speech, the combined-microphone approach significantly outperforms the single- microphone approach.
Journal ArticleDOI

Recent innovations in speech-to-text transcription at SRI-ICSI-UW

TL;DR: It is shown that acoustic adaptation can be improved by predicting the optimal regression class complexity for a given speaker, and speech modeling innovations include the use of a syntax-motivated almost-parsing language model, as well as principled vocabulary-selection techniques.