Comparative experiments to evaluate the use of syllables for large-vocabulary automatic speech recognition

Tolba, Hesham; Azmi, M.M.

doi:10.1109/iccsit.2009.5234953

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Automatic Speech Recognition1

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2012

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“…Hesham Tolba et al [59] motivated the use of syllables to enhance the performance of automatic speech recognition (ASR) systems when dealing with large-vocabulary speech. Arabic and English are considered to test the proposed Approach using The HiddenMarkov Model Toolkit (HTK).…”

Section: Automatic Speech Recognitionmentioning

confidence: 99%

SignsWorld: Deeping into the Silence World and Hearing Its Signs (State of the Art)

Riad¹

2012

IJCSIT

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Automatic speech processing systems are employed more and more often in real environments. Although the underlying speech technology is mostly language independent, differences between languages with respect to their structure and grammar have substantial effect on the recognition systems performance. In this paper, we present a review of the latest developments in the sign language recognition research in general and in the Arabic sign language (ArSL) in specific. This paper also presents a general framework for improving the deaf community communication with the hearing people that is called SignsWorld. The overall goal of the SignsWorld project is to develop a vision-based technology for recognizing and translating continuous Arabic sign language ArSL.

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Section: Automatic Speech Recognitionmentioning

confidence: 99%

SignsWorld: Deeping into the Silence World and Hearing Its Signs (State of the Art)

Riad¹

2012

IJCSIT

View full text Add to dashboard Cite

show abstract

Comparative experiments to evaluate the use of syllables for large-vocabulary automatic speech recognition

Cited by 1 publication

References 6 publications

SignsWorld: Deeping into the Silence World and Hearing Its Signs (State of the Art)

SignsWorld: Deeping into the Silence World and Hearing Its Signs (State of the Art)

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