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A speech translation system would typically integrate the following three software technologies: automatic speech recognition (ASR), machine translation (MT) and voice synthesis (TTS). The speaker of language A speaks into a microphone and the speech recognition module recognizes the utterance.
Some speech recognition systems require "training" (also called "enrollment") where an individual speaker reads text or isolated vocabulary into the system. The system analyzes the person's specific voice and uses it to fine-tune the recognition of that person's speech, resulting in increased accuracy.
A voice connection such as a telephone, cellphone, or computer microphone is used to send the voice to the operator, and the realtime text is transmitted back over a modem, Internet, or other data connection. In some countries, CART may be referred to as Palantype, Velotype, STTR (speech-to-text reporting).
Travelling: Real time mobile translation can help people travelling to a foreign country to make themselves understood or understand others. Business networking: Conducting discussions with (potential) foreign customers using mobile translation saves time and finances, and is instantaneous. Real time mobile translation is a much lower cost ...
The following table compares the number of languages which the following machine translation programs can translate between. (Moses and Moses for Mere Mortals allow you to train translation models for any language pair, though collections of translated texts (parallel corpus) need to be provided by the user.
GNMT's proposed architecture of system learning was first tested on over a hundred languages supported by Google Translate. [2] With the large end-to-end framework, the system learns over time to create better, more natural translations. [1] GNMT attempts to translate whole sentences at a time, rather than just piece by piece. [1]
A DMT system is designed for a specific source and target language pair and the translation unit of which is usually a word. Translation is then performed on representations of the source sentence structure and meaning respectively through syntactic and semantic transfer approaches. A transfer-based machine translation system involves three ...
Using a voice recognition system and a database, a robotic voice will recite the translation in the desired language. [4] Google's stated aim is to translate the entire world's information. Roya Soleimani, a spokesperson for Google, said during a 2013 interview demonstrating the translation app on a smartphone, "You can have access to the world ...