Zobrazeno 1 - 10
of 180
pro vyhledávání: '"David A Mortensen"'
Autor:
Barbara Baraibar, Ebony G Murrell, Brosi A Bradley, Mary E Barbercheck, David A Mortensen, Jason P Kaye, Charles M White
Publikováno v:
PLoS ONE, Vol 15, Iss 7, p e0235868 (2020)
Cover crop mixtures can provide multiple ecosystem services but provisioning of these services is contingent upon the expression of component species in the mixture. From the same seed mixture, cover crop mixture expression varied greatly across farm
Externí odkaz:
https://doaj.org/article/3d47c955a9cb45f2a2fa54cb23926dd4
Autor:
Alwyn Williams, Mitchell C Hunter, Melanie Kammerer, Daniel A Kane, Nicholas R Jordan, David A Mortensen, Richard G Smith, Sieglinde Snapp, Adam S Davis
Publikováno v:
PLoS ONE, Vol 11, Iss 8, p e0160974 (2016)
Yield stability is fundamental to global food security in the face of climate change, and better strategies are needed for buffering crop yields against increased weather variability. Regional- scale analyses of yield stability can support robust inf
Externí odkaz:
https://doaj.org/article/d2ee4b02ec404395b27c86b4eaf46063
Autor:
Jordan Picone, David R. Mortensen
Publikováno v:
Linguistics of the Tibeto-Burman Area. 44:183-208
East Tusom is a Tibeto-Burman language of Manipur, India, belonging to the Tangkhulic group. While it shares some innovations with the other Tangkhulic languages, it differs markedly from “Standard Tangkhul” (which is based on the speech of Ukhru
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::4058fbd361a56eb63095de691aecfbd5
https://doi.org/10.1075/ltba.21009.mor
https://doi.org/10.1075/ltba.21009.mor
Publikováno v:
Interspeech 2022.
Most recent speech recognition models rely on large supervised datasets, which are unavailable for many low-resource languages. In this work, we present a speech recognition pipeline that does not require any audio for the target language. The only a
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::3f8311823181d2597b6e880cc1b6f3c2
https://doi.org/10.21437/interspeech.2022-10712
https://doi.org/10.21437/interspeech.2022-10712
Developing Automatic Speech Recognition (ASR) for low-resource languages is a challenge due to the small amount of transcribed audio data. For many such languages, audio and text are available separately, but not audio with transcriptions. Using text
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e39eb001a4b1eeb25bc851d9b823bbff
http://arxiv.org/abs/2207.09889
http://arxiv.org/abs/2207.09889
Publikováno v:
Restoration Ecology. 28:869-879
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::271938e018d6b3c799d393b0baff767a
https://doi.org/10.1111/rec.13141
https://doi.org/10.1111/rec.13141
Autor:
Jess M. Bunchek, John M. Wallace, Barbara A. Scott, William S. Curran, Mark J. VanGessel, David A. Mortensen
Publikováno v:
Weed Science. 68:534-544
Intensified cover-cropping practices are increasingly viewed as a herbicide-resistance management tool but clear distinction between reactive and proactive resistance management performance targets is needed. We evaluated two proactive performance ta
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::c9ad6b7144bf6342fae42f89734ecda1
https://doi.org/10.1017/wsc.2020.49
https://doi.org/10.1017/wsc.2020.49
Publikováno v:
AAAI
Automatic phonemic transcription tools are useful for low-resource language documentation. However, due to the lack of training sets, only a tiny fraction of languages have phonemic transcription tools. Fortunately, multilingual acoustic modeling pro
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::2b829e292282409fdd73a90bd84612f6
https://doi.org/10.1609/aaai.v34i05.6341
https://doi.org/10.1609/aaai.v34i05.6341
Publikováno v:
Interspeech 2021.
There is growing interest in ASR systems that can recognize phones in a language-independent fashion. There is additionally interest in building language technologies for low-resource and endangered languages. However, there is a paucity of realistic
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::9300b5dd40898d2cb261e256d6b76076
https://doi.org/10.21437/interspeech.2021-1435
https://doi.org/10.21437/interspeech.2021-1435
Publikováno v:
ICASSP
Phone Recognition is one of the most important tasks in the field of multilingual speech recognition, especially for low-resource languages whose orthographies are not available. However, most speech recognition datasets so far only focus on high-res
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::a6071ae800278854acf41ad80bcd5c30
https://doi.org/10.1109/icassp39728.2021.9413720
https://doi.org/10.1109/icassp39728.2021.9413720