Zobrazeno 1 - 10 of 17 pro vyhledávání: '"Amr El-Desoky Mousa"'
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Akademický článek
I Hear You Eat and Speak: Automatic Recognition of Eating Condition and Food Type, Use-Cases, and Impact on ASR Performance.
Autor: Simone Hantke, Felix Weninger, Richard Kurle, Fabien Ringeval, Anton Batliner, Amr El-Desoky Mousa, Björn Schuller
Publikováno v: PLoS ONE, Vol 11, Iss 5, p e0154486 (2016)
We propose a new recognition task in the area of computational paralinguistics: automatic recognition of eating conditions in speech, i. e., whether people are eating while speaking, and what they are eating. To this end, we introduce the audio-visua
Externí odkaz: https://doaj.org/article/76a5bc90028e4faeb68a685aa5008b5b
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4
Sentiment analysis and opinion mining: on optimal parameters and performances
Autor: Björn Schuller, Vasileios Vryniotis, Amr El-Desoky Mousa
Publikováno v: Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery. 5:255-263
Sentiment analysis is the task of identifying the polarity and subjectivity of documents using a combination of machine learning, information retrieval, and natural language processing techniques. The problem is studied within the scope of statistica
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::94545430d38141fb3478870924a639cd
https://doi.org/10.1002/widm.1159
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5
Contextual Bidirectional Long Short-Term Memory Recurrent Neural Network Language Models: A Generative Approach to Sentiment Analysis
Autor: Björn Schuller, Amr El-Desoky Mousa
Publikováno v: EACL (1)
Scopus-Elsevier
Traditional learning-based approaches to sentiment analysis of written text use the concept of bag-of-words or bag-of-n-grams, where a document is viewed as a set of terms or short combinations of terms disregarding grammar rules or word order. Novel
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::d26bb3bc808804760c45ecdd3c05b8d7
https://doi.org/10.18653/v1/e17-1096
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7
I Hear You Eat and Speak: Automatic Recognition of Eating Condition and Food Type, Use-Cases, and Impact on ASR Performance
Autor: Amr El-Desoky Mousa, Felix Weninger, Fabien Ringeval, Björn Schuller, Richard Kurle, Anton Batliner, Simone Hantke
Publikováno v: PLoS ONE, Vol 11, Iss 5, p e0154486 (2016)
PLoS ONE
We propose a new recognition task in the area of computational paralinguistics: automatic recognition of eating conditions in speech, i. e., whether people are eating while speaking, and what they are eating. To this end, we introduce the audio-visua
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e53e28447bc9f9a8bfd1f14a51f9ec92
http://europepmc.org/articles/PMC4866718?pdf=render
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8
Improved strategies for a zero oov rate LVCSR system
Autor: Ralf Schlüter, M. Ali Basha Shaik, Hermann Ney, Amr El-Desoky Mousa, Stefan Hahn
Publikováno v: ICASSP
In this work, multiple hierarchical language modeling strategies for a zero OOV rate large vocabulary continuous speech recognition system are investigated. In our previously proposed hierarchical approach, a full-word language model and a context in
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::0c3e4e3ba8539ba2e2d82892e41c897d
https://doi.org/10.1109/icassp.2015.7178932
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9
The RWTH Large Vocabulary Arabic Handwriting Recognition System
Autor: Michal Kozielski, Mahdi Hamdani, Hermann Ney, Patrick Doetsch, Amr El-Desoky Mousa
Publikováno v: Document Analysis Systems
This paper describes the RWTH system for large vocabulary Arabic handwriting recognition. The recognizer is based on Hidden Markov Models (HMMs) with state of the art methods for visual/language modeling and decoding. The feature extraction is based
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::88f8192b4131aab4b87dcbac5540502f
https://doi.org/10.1109/das.2014.61
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10
Open Vocabulary Arabic Handwriting Recognition Using Morphological Decomposition
Autor: Amr El-Desoky Mousa, Hermann Ney, Mahdi Hamdani
Publikováno v: ICDAR
The use of Language Models (LMs) is a very important component in large and open vocabulary recognition systems. This paper presents an open-vocabulary approach for Arabic handwriting recognition. The proposed approach makes use of Arabic word decomp
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::942be042dacb0037890797eac84d2e6c
https://doi.org/10.1109/icdar.2013.63
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