• International Journal of Computer Science & Network Security
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• v.21 no.3
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• pp.37-40
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• 2021

This paper presents a design of a speech to sign language converter for deaf and hard of hearing people. The device is low-cost, low-power consumption, and it can be able to work entirely offline. The speech recognition is implemented using an open-source API, Pocketsphinx library. In this work, we proposed a context-oriented language model, which measures the similarity between the recognized speech and the predefined speech to decide the output. The output speech is selected from the recommended speech stored in the database, which is the best match to the recognized speech. The proposed context-oriented language model can improve the speech recognition rate by 21% for working entirely offline. A decision module based on determining the similarity between the two texts using Levenshtein distance decides the output sign language. The output sign language corresponding to the recognized speech is generated as a set of sequential images. The speech to sign language converter is deployed on a Raspberry Pi Zero board for low-cost deaf assistive devices.

• International Journal of Computer Science & Network Security
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• v.24 no.2
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• pp.25-30
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• 2024

Various new technologies and aiding instruments are always being introduced for the betterment of the challenged. This project focuses on aiding the mute in expressing their views and ideas in a much efficient and effective manner thereby creating their own place in this world. The proposed system focuses on using various gestures traced into texts which could in turn be transformed into speech. The gesture identification and mapping is performed by the Kinect device, which is found to cost effective and reliable. A suitable text to speech convertor is used to translate the texts generated from Kinect into a speech. The proposed system though cannot be applied to man-to-man conversation owing to the hardware complexities, but could find itself very much of use under addressing environments such as auditoriums, classrooms, etc

• MALSORI
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• no.35_36
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• pp.189-209
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• 1998

This study discusses Korean speech database that has been designed and constructed for common use, especially focusing on designing a list of words or sentences that covers various phonological environments. As the results, PBW(Phonetically Balanced words) and PBS(Phonetically Balanced Sentences) was selected from balanced text corpus using maximum entropy method. And, implemented workbench for spoken language data acquisition is presented in this paper. The workbench consists of grapheme to phoneme converter, utterance list selection module, speech data editing module, multi-layer labelling module, and phoneme context search module.