Results 11 to 20 of about 19,826 (210)

automatic speech recognition [PDF]

, 2011
Automatic speech recognition (ASR) systems convert speech from a recorded audio signal to text. Humans convert words to speech with their speech production mechanism. An ASR system aims to infer those original words given the observable signal. The most common and as of today best method is the probabilistic approach. A speech signal corresponds to any
Rainer E. Gruhn, Wolfgang Minker, Satoshi Nakamura   +2 more
openaire   +2 more sources

Integrating morphology into automatic speech recognition

2009 IEEE Workshop on Automatic Speech Recognition & Understanding, 2009
This paper proposes a novel approach to integrate the morphology as a model into an automatic speech recognition (ASR) system for morphologically rich languages. The high out-of-vocabulary (OOV) word rates have been a major challenge for ASR in morphologically productive languages.
Hasim Sak, Murat Saraclar, Tunga Güngör   +2 more
openaire   +3 more sources

SVMs for Automatic Speech Recognition: A Survey [PDF]

, 2007
Hidden Markov Models (HMMs) are, undoubtedly, the most employed core technique for Automatic Speech Recognition (ASR). Nevertheless, we are still far from achieving high-performance ASR systems. Some alternative approaches, most of them based on Artificial Neural Networks (ANNs), were proposed during the late eighties and early nineties.
Solera Ureña, R., Padrell Sendra, J., Martín Iglesias, D., Gallardo Antolín, Ascensión, Peláez Moreno, Carmen, Díaz de María, Fernando   +5 more
openaire   +3 more sources

Modelling stem cell differentiation related processes—A practical overview for biologists

FEBS Letters, EarlyView.
Stem cell differentiation is complex and difficult to control experimentally. This review introduces suitable computational modelling approaches that can support stem cell research, from mechanistic ODE and abstract models to multiscale and deep learning methods.
Ricco Zeegelaar, Xinqi Yan, Lucas F. Jansen Klomp, Stefano Schivo, Janine N. Post   +4 more
wiley   +1 more source

Morphosyntactic Resources for Automatic Speech Recognition

Proceedings of the Language Resources and Evaluation Conference, 2008
Texts generated by automatic speech recognition (ASR) systems have some specificities, related to the idiosyncrasies of oral productions or the principles of ASR systems, that make them more difficult to exploit than more conventional natural language written texts.
Huet, Stéphane, Gravier, Guillaume, Sébillot, Pascale   +2 more
openaire   +3 more sources

PAK1 activation drives divergent resistance mechanisms to aromatase inhibition and tamoxifen in a luminal: A breast cancer model

Molecular Oncology, EarlyView.
Breast cancer remains a major cause of cancer death in women, frequently developing endocrine therapy resistance. This study demonstrates that upregulated p21‐activated kinase 1 (PAK1) activity drives resistance to tamoxifen and long‐term estrogen deprivation in ER+ breast cancer models.
Luisa Schwarzmüller, Janina Müller, Efstathios‐Iason Vlachavas, Lukas Beumers, Lena Fleischhacker, Sara Burmester, Angelika Wörner, Sabine Karolus, Dominic Helm, Cindy Körner, Stefan Wiemann   +10 more
wiley   +1 more source

SNR features for automatic speech recognition [PDF]

2009 IEEE Workshop on Automatic Speech Recognition & Understanding, 2009
When combined with cepstral normalisation techniques, the features normally used in Automatic Speech Recognition are based on Signal to Noise Ratio (SNR). We show that calculating SNR from the outset, rather than relying on cepstral normalisation to produce it, gives features with a number of practical and mathematical advantages over power-spectral ...
openaire   +2 more sources

Paclitaxel induces NM2‐dependent cellular contraction through GEF‐H1 dissociation from microtubules and RhoA/ROCK activation in cancer cells

Molecular Oncology, EarlyView.
Taxanes are widely used chemotherapeutics whose effects on cellular mechanics remain poorly understood. We show that paclitaxel induces rapid cellular contraction by promoting GEF‐H1 dissociation from microtubules and non‐muscle myosin II activation through RhoA/ROCK.
Gloria Asensio‐Juárez, Rafael Pérez‐Díaz, Hugo Ramos‐Solano, Marina Garrido‐Casado, Vanessa C. Talayero, Miguel Vicente‐Manzanares   +5 more
wiley   +1 more source

Automatic Speech Recognition for Hindi

CoRR
Automatic speech recognition (ASR) is a key area in computational linguistics, focusing on developing technologies that enable computers to convert spoken language into text. This field combines linguistics and machine learning. ASR models, which map speech audio to transcripts through supervised learning, require handling real and unrestricted text ...
Anish Saha, A. G. Ramakrishnan
openaire   +3 more sources

Spatial heterogeneity of hotspot mutations and clonal relatedness in ovarian endometrioid carcinoma

Molecular Oncology, EarlyView.
Spatially resolved analysis revealed heterogeneous distributions of selected cancer‐associated mutations within ovarian endometrioid carcinomas. Shared mutations between paired endometrial and ovarian tumors supported clonal relatedness. These findings highlight the value of sampling multiple tumor regions when interpreting molecular profiles ...
Takahito Ashihara, Kosuke Murakami, Shiro Takamatsu, Akiko Kanto, Seiichi Mori, Tomoyuki Otani, Kazuko Sakai, Yasushi Kotani, Kazuto Nishio, Kaoru Abiko, Noriomi Matsumura   +10 more
wiley   +1 more source