scholarly journals Goal‐directed speech in a spoken language system

1989 ◽  
Vol 86 (S1) ◽  
pp. S76-S76
Author(s):  
Alexander I. Rudnicky
Keyword(s):  
Spoken Language ◽  
Language System

Toward a real-time spoken language system using commercial hardware

1990 ◽  
Author(s):  
Steve Austin ◽  
Pat Peterson ◽  
Paul Placeway ◽  
Richard Schwartz ◽  
Jeff Vandergrift
Keyword(s):  
Real Time ◽  
Spoken Language ◽  
Language System

scholarly journals The BBN Spoken Language System

1989 ◽  
Author(s):  
Sean Boisen ◽  
Yen-Lu Chow ◽  
Andrew Haus ◽  
Robert Ingria ◽  
Salim Roukas ◽  
...  
Keyword(s):  
Spoken Language ◽  
Language System

scholarly journals A new technology on translating Indonesian spoken language into Indonesian sign language system

2021 ◽  
Vol 11 (4) ◽  
pp. 3338
Author(s):  
Risky Aswi Ramadhani ◽  
I Ketut Gede Dharma Putra ◽  
Made Sudarma ◽  
Ida Ayu Dwi Giriantari
Keyword(s):  
Speech Recognition ◽  
Success Rate ◽  
Sign Language ◽  
Text Processing ◽  
New Technology ◽  
Confusion Matrix ◽  
Spoken Language ◽  
Language System ◽  
The People

People with hearing disabilities are those who are unable to hear, resulted in their disability to communicate using spoken language. The solution offered in this research is by creating a one way translation technology to interpret spoken language to Indonesian sign language system (SIBI). The mechanism applied here is by catching the sentences (audio) spoken by common society to be converted to texts, by using speech recognition. The texts are then processed in text processing to select the input texts. The next stage is stemming the texts into prefixes, basic words, and suffixes. Each words are then being indexed and matched to SIBI. Afterwards, the system will arrange the words into SIBI sentences based on the original sentences, so that the people with hearing disabilities can get the information contained within the spoken language. This technology success rate were tested using Confusion Matrix, which resulted in precision value of 76%, accuracy value of 78%, and recall value of 79%. This technology has been tested in SMP-LB Karya Mulya on the 7th grader students with the total of 9 students. From the test, it is obtained that 86% of students stated that this technology runs very well.

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