nltk.translate package

Submodules

• nltk.translate.api module
  • AlignedSent
    • AlignedSent.__init__()
    • AlignedSent.alignment
    • AlignedSent.invert()
    • AlignedSent.mots
    • AlignedSent.words
  • Alignment
    • Alignment.__new__()
    • Alignment.fromstring()
    • Alignment.invert()
    • Alignment.range()
  • PhraseTable
    • PhraseTable.__init__()
    • PhraseTable.add()
    • PhraseTable.translations_for()
  • PhraseTableEntry
    • PhraseTableEntry.__new__()
    • PhraseTableEntry.log_prob
    • PhraseTableEntry.trg_phrase
• nltk.translate.bleu_score module
  • Fraction
    • Fraction.__new__()
    • Fraction.denominator
    • Fraction.numerator
  • SmoothingFunction
    • SmoothingFunction.__init__()
    • SmoothingFunction.method0()
    • SmoothingFunction.method1()
    • SmoothingFunction.method2()
    • SmoothingFunction.method3()
    • SmoothingFunction.method4()
    • SmoothingFunction.method5()
    • SmoothingFunction.method6()
    • SmoothingFunction.method7()
  • brevity_penalty()
  • closest_ref_length()
  • corpus_bleu()
  • modified_precision()
  • sentence_bleu()
• nltk.translate.chrf_score module
  • chrf_precision_recall_fscore_support()
  • corpus_chrf()
  • sentence_chrf()
• nltk.translate.gale_church module
  • LanguageIndependent
    • LanguageIndependent.AVERAGE_CHARACTERS
    • LanguageIndependent.PRIORS
    • LanguageIndependent.VARIANCE_CHARACTERS
  • align_blocks()
  • align_log_prob()
  • align_texts()
  • erfcc()
  • norm_cdf()
  • norm_logsf()
  • parse_token_stream()
  • split_at()
  • trace()
• nltk.translate.gdfa module
  • grow_diag_final_and()
• nltk.translate.gleu_score module
  • corpus_gleu()
  • sentence_gleu()
• nltk.translate.ibm1 module
  • Notations
  • References
  • IBMModel1
    • IBMModel1.__init__()
    • IBMModel1.align()
    • IBMModel1.align_all()
    • IBMModel1.prob_alignment_point()
    • IBMModel1.prob_all_alignments()
    • IBMModel1.prob_t_a_given_s()
    • IBMModel1.set_uniform_probabilities()
    • IBMModel1.train()
• nltk.translate.ibm2 module
  • Notations
  • References
  • IBMModel2
    • IBMModel2.__init__()
    • IBMModel2.align()
    • IBMModel2.align_all()
    • IBMModel2.maximize_alignment_probabilities()
    • IBMModel2.prob_alignment_point()
    • IBMModel2.prob_all_alignments()
    • IBMModel2.prob_t_a_given_s()
    • IBMModel2.set_uniform_probabilities()
    • IBMModel2.train()
  • Model2Counts
    • Model2Counts.__init__()
    • Model2Counts.update_alignment()
    • Model2Counts.update_lexical_translation()
• nltk.translate.ibm3 module
  • Notations
  • References
  • IBMModel3
    • IBMModel3.__init__()
    • IBMModel3.maximize_distortion_probabilities()
    • IBMModel3.prob_t_a_given_s()
    • IBMModel3.reset_probabilities()
    • IBMModel3.set_uniform_probabilities()
    • IBMModel3.train()
  • Model3Counts
    • Model3Counts.__init__()
    • Model3Counts.update_distortion()
• nltk.translate.ibm4 module
  • Terminology
  • Notations
  • References
  • IBMModel4
    • IBMModel4.__init__()
    • IBMModel4.maximize_distortion_probabilities()
    • IBMModel4.model4_prob_t_a_given_s()
    • IBMModel4.prob_t_a_given_s()
    • IBMModel4.reset_probabilities()
    • IBMModel4.set_uniform_probabilities()
    • IBMModel4.train()
  • Model4Counts
    • Model4Counts.__init__()
    • Model4Counts.update_distortion()
• nltk.translate.ibm5 module
  • Terminology
  • Notations
  • References
  • IBMModel5
    • IBMModel5.MIN_SCORE_FACTOR
    • IBMModel5.__init__()
    • IBMModel5.hillclimb()
    • IBMModel5.maximize_vacancy_probabilities()
    • IBMModel5.prob_t_a_given_s()
    • IBMModel5.prune()
    • IBMModel5.reset_probabilities()
    • IBMModel5.sample()
    • IBMModel5.set_uniform_probabilities()
    • IBMModel5.train()
  • Model5Counts
    • Model5Counts.__init__()
    • Model5Counts.update_vacancy()
  • Slots
    • Slots.__init__()
    • Slots.occupy()
    • Slots.vacancies_at()
• nltk.translate.ibm_model module
  • AlignmentInfo
    • AlignmentInfo.__init__()
    • AlignmentInfo.alignment
    • AlignmentInfo.center_of_cept()
    • AlignmentInfo.cepts
    • AlignmentInfo.fertility_of_i()
    • AlignmentInfo.is_head_word()
    • AlignmentInfo.previous_cept()
    • AlignmentInfo.previous_in_tablet()
    • AlignmentInfo.score
    • AlignmentInfo.src_sentence
    • AlignmentInfo.trg_sentence
    • AlignmentInfo.zero_indexed_alignment()
  • Counts
    • Counts.__init__()
    • Counts.update_fertility()
    • Counts.update_lexical_translation()
    • Counts.update_null_generation()
  • IBMModel
    • IBMModel.MIN_PROB
    • IBMModel.__init__()
    • IBMModel.best_model2_alignment()
    • IBMModel.hillclimb()
    • IBMModel.init_vocab()
    • IBMModel.maximize_fertility_probabilities()
    • IBMModel.maximize_lexical_translation_probabilities()
    • IBMModel.maximize_null_generation_probabilities()
    • IBMModel.neighboring()
    • IBMModel.prob_of_alignments()
    • IBMModel.prob_t_a_given_s()
    • IBMModel.reset_probabilities()
    • IBMModel.sample()
    • IBMModel.set_uniform_probabilities()
  • longest_target_sentence_length()
• nltk.translate.meteor_score module
  • align_words()
  • exact_match()
  • meteor_score()
  • single_meteor_score()
  • stem_match()
  • wordnetsyn_match()
• nltk.translate.metrics module
  • alignment_error_rate()
• nltk.translate.nist_score module
  • corpus_nist()
  • nist_length_penalty()
  • sentence_nist()
• nltk.translate.phrase_based module
  • extract()
  • phrase_extraction()
• nltk.translate.ribes_score module
  • corpus_ribes()
  • find_increasing_sequences()
  • kendall_tau()
  • position_of_ngram()
  • sentence_ribes()
  • spearman_rho()
  • word_rank_alignment()
• nltk.translate.stack_decoder module
  • StackDecoder
    • StackDecoder.__init__()
    • StackDecoder.beam_threshold
    • StackDecoder.compute_future_scores()
    • StackDecoder.distortion_factor
    • StackDecoder.distortion_score()
    • StackDecoder.expansion_score()
    • StackDecoder.find_all_src_phrases()
    • StackDecoder.future_score()
    • StackDecoder.stack_size
    • StackDecoder.translate()
    • StackDecoder.valid_phrases()
    • StackDecoder.word_penalty

Module contents

Experimental features for machine translation. These interfaces are prone to change.

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