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  2. The Interpretive Theory of Translation - Wikipedia

    en.wikipedia.org/wiki/The_Interpretive_Theory_of...

    ITT’s main objective is to study translation, but by doing so, it sheds light on the workings of language and communication. As a holistic model of translation, ITT covers the various stages of the translation process, including readers’ expectations and needs. A number of other models [15] study the process from specific angles and add a ...

  3. Organon model - Wikipedia

    en.wikipedia.org/wiki/Organon_model

    The organon model [1] [2]: 35 The organon model is a model of communication by German psychologist and linguist Karl Ludwig Bühler (1879 – 1963). It was published in German in 1934. [1] and not translated into English until 1990. [2] In it he defined the functions of communication according to which linguistic communication can be described.

  4. Comparison of different machine translation approaches

    en.wikipedia.org/wiki/Comparison_of_different...

    A rendition of the Vauquois triangle, illustrating the various approaches to the design of machine translation systems.. The direct, transfer-based machine translation and interlingual machine translation methods of machine translation all belong to RBMT but differ in the depth of analysis of the source language and the extent to which they attempt to reach a language-independent ...

  5. Comparison of machine translation applications - Wikipedia

    en.wikipedia.org/wiki/Comparison_of_machine...

    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.

  6. Neural machine translation - Wikipedia

    en.wikipedia.org/wiki/Neural_machine_translation

    These models differ from an encoder-decoder NMT system in a number of ways: [35]: 1 Generative language models are not trained on the translation task, let alone on a parallel dataset. Instead, they are trained on a language modeling objective, such as predicting the next word in a sequence drawn from a large dataset of text.

  7. Seq2seq - Wikipedia

    en.wikipedia.org/wiki/Seq2seq

    Shannon's diagram of a general communications system, showing the process by which a message sent becomes the message received (possibly corrupted by noise). seq2seq is an approach to machine translation (or more generally, sequence transduction) with roots in information theory, where communication is understood as an encode-transmit-decode process, and machine translation can be studied as a ...

  8. Whisper (speech recognition system) - Wikipedia

    en.wikipedia.org/wiki/Whisper_(speech...

    Whisper is a machine learning model for speech recognition and transcription, created by OpenAI and first released as open-source software in September 2022. [2]It is capable of transcribing speech in English and several other languages, and is also capable of translating several non-English languages into English. [1]

  9. IBM alignment models - Wikipedia

    en.wikipedia.org/wiki/IBM_alignment_models

    The original work on statistical machine translation at IBM proposed five models, and a model 6 was proposed later. The sequence of the six models can be summarized as: Model 1: lexical translation; Model 2: additional absolute alignment model; Model 3: extra fertility model; Model 4: added relative alignment model; Model 5: fixed deficiency ...