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Słownik AI

Kompletny słownik sztucznej inteligencji

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kategorie
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podkategorie
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pojęcia
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Machine Translation (MT)

Computational process that automatically translates text from a source language to a target language without human intervention, using algorithms and linguistic models.

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Neural Machine Translation (NMT)

Machine translation approach that uses deep neural networks to directly model the conditional probability of translation, surpassing traditional statistical systems.

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Statistical Machine Translation (SMT)

Translation method based on statistical models learned from large bilingual corpora, primarily using probabilistic language and translation models.

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Attention Mechanism

Technique that allows NMT models to selectively focus on different parts of the source text when generating each target word, significantly improving translation quality.

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Transformer Architecture

Neural network architecture entirely based on attention mechanisms, eliminating recurrence and convolutions, becoming the standard for modern NMT systems.

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BLEU Score

Automatic evaluation metric for machine translation that compares generated translations to human references by measuring n-gram precision.

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Parallel Corpus

Collection of bilingual texts where each sentence in the source language is aligned with its corresponding translation in the target language, essential for training MT systems.

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Back-Translation

Data augmentation technique where a trained NMT model translates target monolingual texts to the source language, creating synthetic data to improve performance.

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Zero-shot Translation

Capacity of multilingual models to translate between language pairs never seen during training, using a pivot language as an implicit intermediary.

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Subword Segmentation

Process breaking down words into smaller units (BPE, WordPiece) to handle open vocabulary and improve generalization on rare or unknown words.

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Beam Search

Decoding algorithm simultaneously exploring multiple partial translation hypotheses, selecting the most probable at each step to balance diversity and quality.

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Post-editing

Human review of machine translations to correct errors and improve quality, combining automation efficiency with human linguistic expertise.

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Multilingual NMT

Single system capable of translating between multiple language pairs, sharing parameters to benefit from inter-language knowledge transfer and reduce complexity.

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Language Model

Probabilistic model assigning probabilities to word sequences, used in NMT as a decoding component to evaluate fluency and coherence of generated translations.

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Encoder-Decoder

Neural architecture composed of an encoder processing source text into vector representation and a decoder sequentially generating the target translation.

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Byte-Pair Encoding (BPE)

Data compression algorithm adapted for subword tokenization, creating an optimal vocabulary by iteratively merging the most frequent symbol pairs.

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