An N-gram transducer (NGT) is a type of finite-state transducer that is used to model sequences of words or tokens in natural language processing tasks. It is a probabilistic model that estimates the likelihood of a sequence of words occurring based on the probability of the individual words in the sequence.
An NGT is a mathematical model that represents the probability of a sequence of words or tokens as the product of the probabilities of the individual words or tokens in the sequence. It works by using a set of rules or transitions that define the probability of transitioning from one word or token to another. These transitions are based on the frequencies of the words or tokens in the training data.
NGTs are often used in natural language processing tasks such as language modeling, machine translation, and speech recognition. They can be trained on large corpora of text data to learn the patterns and structures of a particular language or domain. Once trained, they can be used to predict the likelihood of a sequence of words or tokens occurring in a given context.
An N-gram converter is a tool or software program that converts a sequence of words or tokens into a set of N-grams. An N-gram is a contiguous sequence of n items from a given sample of text or speech. For example, in the sentence “I went to the store”, a 2-gram (also known as a bigram) would be a sequence of two words, such as “I went”, “went to”, and “to the”.
An N-gram converter takes a sequence of words or tokens and generates a set of N-grams by breaking the sequence down into contiguous subsequences of length N. The output of the N-gram converter is a set of N-grams that can be used for a variety of purposes, such as language modeling, text classification, or feature extraction.
An N-gram transducer, on the other hand, is a mathematical model that represents the probability of a sequence of words or tokens as the product of the probabilities of the individual words or tokens in the sequence. It is used to estimate the likelihood of a sequence of words occurring based on the probability of the individual words in the sequence. An N-gram transducer can be trained on large corpora of text data to learn the patterns and structures of a particular language or domain, and can be used to predict the likelihood of a sequence of words occurring in a given context.
While an N-gram converter and an N-gram transducer are both related to the concept of N-grams, they serve different purposes and are used in different contexts. The N-gram converter is a tool that breaks a sequence of words or tokens into a set of N-grams, while the N-gram transducer is a probabilistic model that estimates the likelihood of a sequence of words occurring based on the probability of the individual words in the sequence.
Improving unsegmented dialogue turns annotation with n-gram transducers. CD Martínez-Hinarejos, V Tamarit… – 2009 – eprints.pascal-network.org Abstract The statistical models used for dialogue systems need annotated data (dialogues) to infer their statistical parameters. Dialogues are usually annotated in terms of Dialogue Acts (DA). The annotation problem can be attacked with statistical models, that avoid … Cited by 6 – Related articles – Cached – All 2 versions
[PDF] Reduction of the Temporal Complexity of N-gram Transducers for Dialogue Annotation [PDF] from psu.eduV Tamarit, CD Martinez-Hinarejos… – Proceedings of the First …, 2009 – Citeseer Abstract. The annotation of dialogues with Dialogue Acts is important to develop dialogue systems. One way to do this annotation is using a method called N-gram Transducer (NGT), that has shown very good results in unsegmented turns compared with other models, but … Cited by 2 – Related articles – View as HTML – All 2 versions
Inference of Stochastic Finite-State Transducers Using N-Gram Mixtures V Alabau, F Casacuberta, E Vidal… – Pattern Recognition and …, 2007 – Springer … traditional n-gram modelling. The rest of the paper is structured as follows. Section 2 describes the GIATI method for n-gram transducer inference. Section 3 explains the approximation followed to create the mixtures. Next, a series … Cited by 2 – Related articles – BL Direct – All 2 versions
Statistical framework for a spanish spoken dialogue corpus [PDF] from cnrs.frCD Martínez-Hinarejos, JM Benedí… – Speech Communication, 2008 – Elsevier … HMM-based model 2.2. N-gram transducer model 3. Spanish spoken dialogue corpus 4. Experiments and results 4.1. Initial experiments 4.2. … 2.2. N-gram transducer model. The next proposal is the N-gram transducer (NGT) model. … Cited by 15 – Related articles – All 11 versions
A study of a segmentation technique for dialogue act assignation [PDF] from rug.nlCD Martínez-Hinarejos – … of the Eighth International Conference on …, 2009 – dl.acm.org … From this sequence that includes the utterance boundaries, an N-gram can be inferred. We implemented the Viterbi search to work directly on the N-gram that acts as a transducer, and gives the name to the model: N-gram transducers (NGT). … Cited by 3 – Related articles – All 7 versions
GREAT: a finite-state machine translation toolkit implementing a Grammatical Inference Approach for Transducer Inference (GIATI) [PDF] from uni-potsdam.deJ González… – Proceedings of the EACL 2009 Workshop …, 2009 – dl.acm.org … 2.2 Phrase-based n-gram transducers Phrase-based n-gram transducers represent an in- teresting application of the GIATI methodology, where the extended symbols are actually bilingual phrase pairs, and n-gram models … Cited by 4 – Related articles – All 17 versions
Language model combination and adaptation usingweighted finite state transducers [PDF] from mirlab.orgX Liu, MJF Gales, JL Hieronymus… – … Speech and Signal …, 2010 – ieeexplore.ieee.org … A similar issue exists during the composition between compo- nent n-gram transducers in the log-linear combination of equation (4). Hence, it is preferable to dynamically perform the composition, union and compression operations of equation (2) in one single step on-the-fly. … Cited by 2 – Related articles – All 7 versions
Acoustic modelling using continuous rational kernels [PDF] from psu.eduM Layton, M Gales – The Journal of VLSI Signal Processing, 2007 – Springer … KšOi; OjŽ 1/4 1 TiTj 1/21/2Li UUA1 Lj š12Ž where U is a transducer that maps the latent-state acceptors Li and Lj into a high-dimensional feature- space where distances can be calculated. In this paper,n-gram and gappy-n-gram transducers are described. … Cited by 5 – Related articles – BL Direct – All 11 versions
Fitting class-based language models into weighted finite-state transducer framework [PDF] from cmu.eduP Ircing… – Eighth European Conference on Speech …, 2003 – isca-speech.org … transducer composition formula (9) and hence a class-based language model can be rep- resented by a composition of two finite-state transducers T ? V where T realizes a mapping from word-class pairs (wi, ci) to – ln P(wi|ci) and V is a well-known n-gram transducer based on … Cited by 2 – Related articles – All 4 versions
[PDF] Evaluation of the incremental dialogue annotation using N-gram Transducers [PDF] from upm.esCD Martinez-Hinarejos, JMB Vicent Tamarit – lorien.die.upm.es Abstract The annotation of dialogues in terms of Dialogue Acts (DA) is an important task in the development of dialogue systems. Recently, the N-gram Transducers (NGT) technique showed a better performance than other techniques in the annotation of unsegmented … Related articles – View as HTML – All 2 versions
On the Use of N-Gram Transducers for Dialogue Annotation V Tamarit, CD Martínez-Hinarejos… – Spoken Dialogue Systems …, 2011 – Springer The implementation of dialogue systems is one of the most interesting applications of language technologies. Statistical models can be used in this implementation, allowing for a more flexible approach than when using rules defined by a human expert. However, … Related articles
Active learning for dialogue act labelling F Ghigi, V Tamarit, CD Martínez-Hinarejos… – Pattern Recognition and …, 2011 – Springer … where @ is the attaching metasymbol. dialogue model. The automatic annotation method used in this work is the N- Gram Transducer (NGT) annotation model, described in [Tamarit et al., 2009]. We report experiments to find … Related articles – All 2 versions
Round-robin duel discriminative language models in one-pass decoding with on-the-fly error correction [PDF] from 22.214.171.124T Oba, T Hori, A Ito… – Acoustics, Speech and …, 2011 – ieeexplore.ieee.org … the best path. Our baseline system handles two WFSTs with the on-the- fly composition, which are an HMM-state-to-word transducer (ie WFST1 in Fig. 1) and a word n-gram transducer (ie WFST2 in Fig. 1). Our decoder, SOLON … All 4 versions
[PDF] A Weighted Finite State Transducer tutorial [PDF] from idiap.chPN Garner – 2007 – idiap.ch … 6.1 Introduction This section presents a walk-through of the construction of a toy stochastic n-gram transducer. The aim is to make explicit some of the techniques summarised earlier, to introduce other techniques that are more explicit by example, and to warn of potential pitfalls. … Related articles – View as HTML – All 10 versions
[TXT] Rational Kernels [TXT] from nips.ccCCPHM Mohri – International Journal of Foundations of Computer …, 2003 – books.nips.cc … gap in TN; is weighted by . 0 a:e b:e 1 a:a b:b 2 a:a b:b a:e b:e 0 a:e b:e 1 a:a b:b a:e/l b:e/l 2 a:a b:b a:e b:e (a) (b) Figure 3: N-gram transducers (N = 2) defined over the probability semiring. (a) Bigram counter transducer T 2 … Related articles – Cached – All 19 versions
[PDF] Evaluation of HMM-based models for the annotation of unsegmented dialogue turns [PDF] from psu.eduCD Martinez-Hinarejos, JMB Vicent Tamarit – Proceedings of the Seventh …, 2010 – Citeseer … 2009. Improving unsegmented dialogue turns annota- tion with n-gram transducers. In Proceedings of the 23rd Pacific Asia Conference on Language, Information and Computation (PACLIC23), volume 1, pages 345-354, Hong Kong, December. … Related articles – View as HTML – All 4 versions
[PDF] Shallow Semantic Parsing of Persian Sentences [PDF] from mshdiau.ac.irAK Ghalibaf… – 2009 – rahati.mshdiau.ac.ir … Scope and Anaphoric Links in Dynamic Discourse Representation Theory So-Woo Chung and Jungmin Lee Improving Unsegmented Dialogue Turns Annotation with N-gram Transducers Carlos-D. Martínez-Hinarejos, Vicent Tamarit and José-Miguel Benedí 9:50 – 10:30 … Related articles – View as HTML
[BOOK] Spoken dialogue systems technology and design W Minker, GG Lee, S Nakamura… – 2010 – books.google.com … vii Page 8. compare two statistical models for dialogue annotation, a classical Hidden Markov Model and a novel N-gram Transducers model (Tamarit et al., 2010). This latter one should allow for faster data annotation. … On the Use of N-gram Transducers for Dialogue Annotation. … Cited by 3 – Related articles – Library Search – All 2 versions