scholarly journals Scribe-Free Way for the Specially Abled to Write Exams

2021 ◽  
Vol 11 (2) ◽  
pp. 2096-2105
Author(s):  
P. Ezhumalai ◽  
Pacha Shobha Rani ◽  
S. Bharkavi ◽  
S. Charulatha ◽  
Deivala kshmi
Keyword(s):  
Speech Recognition ◽  
Great Difficulty ◽  
Android Application ◽  
Practical Difficulty ◽  
Technical Terms ◽  
Voice Response

The specially-abled face a lot of issues when it comes to taking up exams. They require specific assistance for taking up their exams known as a scribe. However in today’s world finding a scribe is of great difficulty. Even if the scribe is found there are a lot of other practical difficulties while using a scribe to write exams. One such practical difficulty in using a scribe to write exams is that the scribe may not be aware of the technical terms used by the candidate. This causes loss of marks for the candidate if the scribe makes an error. The scribe should also have a legible handwriting which again is a problem. Our project aims at eliminating the need for a scribe and allowing the candidate itself to take up their exams by leveraging the latest technologies such as speech recognition and synthesis. This is achieved with the help of an android application, using which the questions can be stored in a database using administrator login. A separate candidate login is given. The question will be read out to the candidate and the answer will be taken as a voice response.

CARMIE

2017 ◽  
Vol 8 (4) ◽  
pp. 21-37 ◽  
Author(s):  
Joana Lobo ◽  
Liliana Ferreira ◽  
Aníbal JS Ferreira
Keyword(s):  
Heart Failure ◽  
Chronic Disease ◽  
Speech Recognition ◽  
Older People ◽  
Home Environment ◽  
System Architecture ◽  
Usability Study ◽  
Conversational Agent ◽  
Android Application ◽  
Prescribed Medicines

The incidence of chronic diseases is increasing and monitoring patients in a home environment is recommended. Noncompliance with prescribed medication regimens is a concern, especially among older people. Heart failure is a chronic disease that requires patients to follow strict medication plans permanently. With the objective of helping these patients managing information about their medicines and increasing adherence, the personal medication advisor CARMIE was developed as a conversational agent capable of interacting, in Portuguese, with users through spoken natural language. The system architecture is based on a language parser, a dialog manager, and a language generator, integrated with already existing tools for speech recognition and synthesis. All modules work together and interact with the user through an Android application, supporting users to manage information about their prescribed medicines. The authors also present a preliminary usability study and further considerations on CARMIE.

scholarly journals SISTEM PAKAR DIAGNOSA KERUSAKAN MOTOR KAWASAKI KLX150 MENGGUNAKAN METODE CASE-BASED REASONING DENGAN ALGORITMA 3W-JACCARD

2021 ◽  
Vol 8 (01) ◽  
pp. 1-8
Author(s):  
Akhmad Rezki Purnajaya ◽  
Fatma Indriani ◽  
Mohammad Reza Faisal
Keyword(s):  
Speech Recognition ◽  
Statistical Inference ◽  
Training Data ◽  
Case Based Reasoning ◽  
Android Application ◽  
Regional Language ◽  
Black Box Testing ◽  
Local Residents ◽  
Translation Accuracy ◽  
The Voice

Banjar language used in conversation and daily life around the area. So foreigners who come to the regions of South Kalimantan will have difficulty in communicating. Besides, most local residents in the backwoods of South Kalimantan can not use Indonesian language properly, they would be more convenient to use regional language to interact. For that reason we need an Android application can help users to find the translation of a word or phrase whenever and wherever. With the help of Google Voice Search, this application can also listen to the voice of the user to be converted into text and insert into the input translation. Speech recognition of Banjar language required a literacy training data by using the method of statistical inference to make results appropriated. Testing using method of Black Box Testing to measure the percentage of suitability of the results of translation, speech recognition for Indonesian language and speech recognition Banjar language using method of Statistical inference. So the results of translation accuracy 100% and accuracy of speech recognition Indonesian language and Banjar language by 97.85% and 82.74%.

Interactive Voice Response (IVR) Systems as Automatic Speech Recognition (ASR) Comes of Age

1998 ◽  
Vol 42 (4) ◽  
pp. 444-447 ◽  
Author(s):  
Daryle Gardner-Bonneau ◽  
Cristina Delogu ◽  
Chuck Green ◽  
Lydia Volaitis ◽  
Martha Lindeman ◽  
...  
Keyword(s):  
Speech Recognition ◽  
Automatic Speech Recognition ◽  
Interactive Voice Response ◽  
Commercial Use ◽  
The Impact ◽  
Potential Customers ◽  
Workplace Speech ◽  
Ivr Systems ◽  
Made In ◽  
Voice Response

While interactive voice response (IVR) systems were rapidly making their way into the workplace, speech scientists were working hard to improve the performance of automatic speech recognition (ASR) systems to foster their acceptance among potential customers. In the last five years, great strides have been made in this regard, and the commercial use ASR is on the rise. The purpose of this panel is to explore the impact that ASR is (or is not) having on the design of IVR systems that were envisioned originally to operate solely via touch-tone input.

A Method to Improve the Accuracy of Voice Translation by Adding Intentional Spaces

2020 ◽  
Vol 25 (3) ◽  
pp. 93-98
Author(s):  
Kyu-Seok Kim
Keyword(s):  
Speech Recognition ◽  
Real Time ◽  
Recognition System ◽  
Speech Recognition System ◽  
Android Application ◽  
Speech Recognizer ◽  
Translation Systems ◽  
The Web

Real-time voice translation systems receive a speaker s voice and translate their speech into another language. However, the meaning of a whole Korean sentence can be unintentionally changed because Korean words and syllables can be merged or divided by spaces. Therefore, the spaces between the speaker s sentences are occasionally not identified by the speech recognition system, so the translated sentences are sometimes incorrect. This paper presents a methodology to enhance the accuracy of voice translation by adding intentional spaces. An Android application was implemented using Google speech recognizer for Android and Google translator for the Web. The Google speech recognizer app for Android receives the speaker s voice sentences in Korean and shows the text results. Next, the proposed Android application adds spaces when the speaker speaks the dedicated word for the space. Finally, the modified Korean sentences are translated into English by Google translator for the Web. Using this method can enhance interpretation accuracy for translation systems.

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