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The first version was released around the year 2000 under the name EAT, Eudico Annotation Tool. It was renamed to ELAN in 2002. Since then, two to three new versions are released each year. It is developed in the programming language Java with interfaces to platform native media frameworks developed in C, C++, and Objective-C.
The Java Speech API was written before the Java Community Process (JCP) and targeted the Java Platform, Standard Edition (Java SE). Subsequently, the Java Speech API 2 (JSAPI2) was created as JSR 113 under the JCP. This API targets the Java Platform, Micro Edition (Java ME), but also complies with Java SE.
Sphinx is a continuous-speech, speaker-independent recognition system making use of hidden Markov acoustic models and an n-gram statistical language model. It was developed by Kai-Fu Lee . Sphinx featured feasibility of continuous-speech, speaker-independent large-vocabulary recognition, the possibility of which was in dispute at the time (1986).
ANTLR takes as input a grammar that specifies a language and generates as output source code for a recognizer of that language. While Version 3 supported generating code in the programming languages Ada95 , ActionScript , C , C# , Java , JavaScript , Objective-C , Perl , Python , Ruby , and Standard ML , [ 3 ] Version 4 at present targets C# ...
Sign Language Recognition (shortened generally as SLR) is a computational task that involves recognizing actions from sign languages. [1] This is an essential problem to solve especially in the digital world to bridge the communication gap that is faced by people with hearing impairments.
Julius is a speech recognition engine, specifically a high-performance, two-pass large vocabulary continuous speech recognition (LVCSR) decoder software for speech-related researchers and developers. It can perform almost real-time computing (RTC) decoding on most current personal computers (PCs) in 60k word dictation task using word trigram (3 ...
When a research project successfully matched English letters from a keyboard to ASL manual alphabet letters which were simulated on a robotic hand. These technologies translate signed languages into written or spoken language, and written or spoken language to sign language, without the use of a human interpreter.
Facial recognition was the motivation for the creation of eigenfaces. For this use, eigenfaces have advantages over other techniques available, such as the system's speed and efficiency. As eigenface is primarily a dimension reduction method, a system can represent many subjects with a relatively small set of data.