IRSTLM (IRST Language Modeling) Toolkit

Notes:

IRSTLM is a toolkit for building and manipulating statistical language models. It is used to estimate the probability of a sequence of words, given a set of training data. The toolkit includes algorithms for estimating n-gram probabilities, smoothing techniques to smooth out sparse data, and tools for building and manipulating language models. IRSTLM can be used in a variety of natural language processing tasks, such as machine translation, speech recognition, and information retrieval. It is open-source software and is written in C++.

The Bruno Kessler Foundation (FBK) is an international research organization based in Trento, Italy. It was founded in 1988 as the Istituto per la Ricerca Scientifica e Tecnologica (IRST) and was later renamed to its current name in honor of Bruno Kessler, a prominent Italian politician and intellectual. The FBK conducts research in a variety of fields, including information and communication technology, humanities and social sciences, energy and environment, and health and welfare. The FBK-IRST toolkit, also known as IRSTLM, is a tool developed by researchers at the FBK for building and manipulating statistical language models. It is widely used in natural language processing and has been made available as open-source software.

Resources:

Wikipedia:

See also:

Language Modeling & Dialog Systems 2017 | Rule-based Language Modeling | SRILM Toolkit & Dialog Systems 2018

English to Bodo Phrase-Based Statistical Machine Translation
MS Islam, BS Purkayastha – Advanced Computing and Communication …, 2018 – Springer
… Moses can run on both Linux and Windows OS (under Cygwin). 3.3 IRSTLM and KenLM … The Language Model is developed only for the target language using the KenLM and IRSTLM toolkit [16]. IRSTLM is freely available on online and KenLM comes with Moses. 3.4 GIZA ++ …

English to Nepali Statistical Machine Translation System
A Paul, BS Purkayastha – Proceedings of the International Conference on …, 2018 – Springer
… The system is implemented using three different tools like MOSES for decoding, GIZA++ for generating translation model and IRSTLM for estimating target model probability … The input of the GIZA++ and IRSTLM will be the output of preprocessing module …

Quality Translation Enhancement Using Sequence Knowledge and Pruning in Statistical Machine Translation
T Mantoro, J Asian – TELKOMNIKA, 2018 – search.proquest.com
… This study evaluated 28 different parameters in IRSTLM language modeling, which resulting 270 millions experiments, and proposes a sequence evaluation mechanism based on a maximum evaluation of each parameter in producing a good quality translation based on NIST …

Bi-directional Afaan Oromo-English Statistical Machine Translation
Y Solomon, W Endale – researchgate.net
… In this study tri-gram model was used for creating the language model using IRSTLM tool … d for accomplishing the task is Moses for Mere tistical machine translation t toolkits such as IRSTLM Decoder for translation, and hunalign for The procedure followed to come u …

The HistCorp Collection of Historical Corpora and Resources
E Pettersson, B Megyesi – DHN 2018 The Third Conference on …, 2018 – diva-portal.org
… The language models provided on the HistCorp platform were created using the irstlm toolkit5 (Federico et al … Federico, M., Bertoldi, N. and Cettolo, M.: IRSTLM: an open source toolkit for han- dling large scale language models. Proceedings of Interspeech 1618–1621 (2008) …

Data-Driven Pronunciation Modeling of Swiss German Dialectal Speech for Automatic Speech Recognition
M Stadtschnitzer, C Schmidt – Proceedings of the Eleventh International …, 2018 – aclweb.org
… We use a 5-gram model, trained with modified shift beta algorithm with back-off weights using IRSTLM (Federico et al., 2008) and a dictio- nary size of approximately 500,000 words and a language model pruning factor of 10?8. For training of the acoustical model, the …

Grammar Error Detection Tool for Medical Transcription Using Stop Words Parts-of-Speech Tags Ngram Based Model
BR Ganesh, D Gupta, T Sasikala – Proceedings of the Second …, 2018 – Springer
… The corpus was preprocessed and a language model was generated by using an open source toolkit called IRSTLM. The IRSTLM tool takes in a huge chunk of text data and splits it into a set of ngram where the maximum level of n can be set as needed [12] …

Grammar Error Detection Tool for Medical Transcription Using Stop Words Parts-of-Speech Tags Ngram Based
BR Ganesh, D Gupta, T Sasikala – Proceedings of the Second …, 2018 – books.google.com
… The corpus was preprocessed and a language model was generated by using an open source toolkit called IRSTLM. The IRSTLM tool takes in a huge chunk of text data and splits it into a set of ngram where the maximum level of n can be set as needed [12] …

English-Afaan Oromo Statistical Machine Translation
M Meshesha, Y Solomon – researchgate.net
… This software integrates different toolkits such as IRSTLM for language model, Decoder for translation … Moses for mere mortal used for translation process which integrate all necessary tools for machine translation such as IRSTLM, MGIZA++ and decoder …

Experimental Study Of Neural Network-Based Word Alignment Selection Model Trained With Fourier Descriptors
A KARTBAYEV, U TUKEYEV… – … of Theoretical & …, 2018 – search.ebscohost.com
… SMT requires language model (LM) to produce translations. Usually LM is created by the external toolkits like SRILM[10] or IRSTLM[11]. In our experiment, we use the IRSTLM toolkit for the large monolingual corpus. Before …

Resource Creation for Training and Testing of Normalisation Systems for Konkani-English Code-Mixed Social Media Text
A Phadte – International Conference on Applications of Natural …, 2018 – Springer
… 177–180. Association for Computational Linguistics (2007)Google Scholar. 9. Federico, M., Bertoldi, N., Cettolo, M.: IRSTLM: an open source toolkit for handling large scale language models. In: Interspeech, pp. 1618–1621 (2008)Google Scholar. 10 …

Marathi Speech Recognition.
S Paulose, S Nath, K Samudravijaya – SLTU, 2018 – isca-speech.org
… A user can use various kinds of language models using external language model toolkits. In our experiments we used a simple model: bigram language model as estimated by IRSTLM toolkit [10]. The bigram language model was trained using the transcripts of train data alone …

Hierarchical Recurrent Neural Networks for Acoustic Modeling.
J Park, I Choi, Y Boo, W Sung – Interspeech, 2018 – isca-speech.org
… level LM. Greedy decoding does not use any external information except the RNN acoustic model. The trigram word LM was generated with the IRSTLM toolkit [24] included in the KALDI speech recognition tool. We used the …

Enhancing Translation from English to Arabic Using Two-Phase Decoder Translation
A ElMaghraby, A Rafea – Proceedings of SAI Intelligent Systems …, 2018 – Springer
… Using this dataset we created our language model with IRSTLM [11]. All the decoders created from now on are used this language model … Federico, M., Bertoldi, N., Cettolo, M.: IRSTLM: an open source toolkit for handling large scale language models. In: Interspeech, pp …

Continuous Punjabi speech recognition model based on Kaldi ASR toolkit
J Guglani, AN Mishra – International Journal of Speech Technology, 2018 – Springer
… 2. Fig. 2 ASR model using Kaldi toolkit. Kaldi uses a FST-based framework; therefore, any language model can be applied which supports FST. One can easily implement N-gram model using the IRSTLM or SRILM toolkit which is included in their recipe (Lee et al. 2001) …

Language Features for Automated Evaluation of Cognitive Behavior Psychotherapy Sessions.
N Flemotomos, VR Martinez, J Gibson, DC Atkins… – Interspeech, 2018 – isca-speech.org
… performance. This issue needs further investigation. For the adout set, we used the pipeline described in Section 3.1. For the role matching module, 3-gram LMs with Witten- Bell smoothing were constructed with IRSTLM [27]. The …

Colorless green recurrent networks dream hierarchically
K Gulordava, P Bojanowski, E Grave, T Linzen… – arXiv preprint arXiv …, 2018 – arxiv.org
… first, a unigram baseline, which picks the most frequent form in the training corpus out of the two candi- date target forms (singular or plural); second, a 5-gram model with Kneser-Ney smoothing (KN, Kneser and Ney, 1995) trained using the IRSTLM package (Federico et al …

Multi-view representation learning via canonical correlation analysis for dysarthric speech recognition
M Kim, B Cao, J Wang – International Conference on Mechatronics and …, 2018 – Springer
… The network parameters were trained using backpropagation through time. The IRSTLM toolkit [26] was used to train bigram phoneme language models … Federico, M., Bertoldi, N., Cettolo, M.: IRSTLM: an open source toolkit for handling large scale language models …

Developing Statistical Machine Translation System for English and Nigerian Languages
II Ayogu, AO Adetunmbi… – Asian Journal of Research …, 2018 – journalajrcos.com
… Each language model is a trigram model trained on the target side monolingual corpus of 50,000 sentences using IRSTLM [23] with modified Kneser-Ney smoothing … Federico M, Bertoldi N, Cettolo M. IRSTLM: An open source toolkit for handling large scale language models …

English to Punjabi statistical machine translation using moses (Corpus Based)
S Jindal, V Goyal, JS Bhullar – Journal of Statistics and …, 2018 – Taylor & Francis
… of the proposed system. It is important for the system to know the language, so that outputs should be structured. The IRSTLM documentation gives a full explanation of the command-line option [8]. 5.3 Training the Translation …

A Study on Effect of Semantic Noise Parameters on Corpus for English–Hindi Statistical Machine Translation
S Maheshwari – Ambient Communications and Computer Systems, 2018 – Springer
… The language models for tasks are 3-grams trained by IRSTLM toolkit. For Moses system, the phrase extraction heuristic is “grow-diag-final,” and the reordering heuristic applied is “msd-bi-directional-fe.” The python code is executed before the tuning process …

Continuous Speech Recognition System for Malayalam Language Using Kaldi
LB Babu, A George, KR Sreelakshmi… – … on Emerging Trends …, 2018 – ieeexplore.ieee.org
… Context depen- dent triphone system and monophone system were developed. The MFCC features and their transformations were used for model generation. Kaldi uses the FST-based framework and the IRSTLM toolkit was used to build the LM model from raw text …

An online English-Khmer hybrid machine translation system.
S Jabin, N Chatterjee, S Samak, K Sokphyrum, J Sola – IJISTA, 2018 – researchgate.net
… phrase-table): Number of phrase tables: 160,790 Number of n-grams in LM (as extracted from /opt/domy/ENGINES/lms/lm-t=kh-l=lm-en-kh-T=irstlm- n=3/irstlm.kh. mm): n-gram for n = 1: 65,980 n-gram for n = 2: 241,470 n-gram

Learning to remember translation history with a continuous cache
Z Tu, Y Liu, S Shi, T Zhang – Transactions of the Association for …, 2018 – MIT Press
Page 1. Learning to Remember Translation History with a Continuous Cache Zhaopeng Tu Tencent AI Lab zptu@tencent.com Yang Liu Tsinghua University liuyang2011@tsinghua. edu.cn Shuming Shi Tencent AI Lab shumingshi@tencent.com …

Acoustic Word Disambiguation with Phonogical Features in Danish ASR
AS Kirkedal – Proceedings of the Fifteenth Workshop on …, 2018 – aclweb.org
… trains a series of GMM models and a DNN model from scratch. We use IRSTLM (Federico et al., 2008) to train a language model (LM) on the training transcripts. We also tried to train a LM on ngram frequency lists calculated …

Hindi-English Code-Switching Speech Corpus
G Sreeram, K Dhawan, R Sinha – arXiv preprint arXiv:1810.00662, 2018 – arxiv.org
… LM. For developing the 3-gram LM, we have employed the IRSTLM toolkit [36] … 192584. [36] Marcello Federico, Nicola Bertoldi, and Mauro Cettolo, “IRSTLM: an open source toolkit for handling large scale lan- guage models,” in Proc …

Robust Speech Recognition for German and Dialectal Broadcast Programmes
M Stadtschnitzer – 2018 – d-nb.info
… 103 A.3 Eesen . . . . . 104 A.4 RNNLM . . . . . 104 A.5 IRSTLM . . . . . 104 A.6 Sequitur-G2P . . . . . 104 viii Page 11. Contents A.7 TheanoLM …

Morphology Injection for English-Malayalam Statistical Machine Translation
S Sreelekha, P Bhattacharyya – Proceedings of the Eleventh …, 2018 – aclweb.org
… Factored model trained on the corpus used for Fact augmented with the word form dictionary for solving noun and verb morphology (Fact-Morph). 1 http://www.statmt.org/moses/ 2https://hlt.fbk.eu/technologies/irstlm-irst-languagemodel ling-toolkit …

Automatic translation of Arabic text-to-Arabic sign language
H Luqman, SA Mahmoud – Universal Access in the Information Society, 2018 – Springer
… Page 9. Universal Access in the Information Society 1 3 [58] and IRSTLM [59]. The synonym words are scored using KenLM, and the closest synonym to the source word in meaning is selected. After the lexical transformation, the rule transformation is applied …

Pipilika N-gram Viewer: An Efficient Large Scale N-gram Model for Bengali
A Ahmad, MR Talha, MR Amin… – … Conference on Bangla …, 2018 – ieeexplore.ieee.org
… [6] M. Federico, N. Bertoldi, and M. Cettolo. 2008. IRSTLM: an open source toolkit for handling large scale language models. In Proceedings of Inter-speech, Brisbane, Australia [7] CD Manning, P. Raghavan and M. Schtze (2008). Introduction to Information Retrieval …

English–Mizo Machine Translation using neural and statistical approaches
A Pathak, P Pakray, J Bentham – Neural Computing and Applications, 2018 – Springer
… to output target sentence. Moses provides support for a number of language modeling toolkits, such as SRILM, KenLM, IRSTLM and RandLM, and offers flexibility to introduce a new such toolkit. Besides, the decoder in Moses …

Definition of requirements for accessing multilingual information opinions
J Derkacz, M Leszczuk, M Grega, A Ko?bia?… – Multimedia Tools and …, 2018 – Springer
… translation algorithms. For machine translation The system will use the state-of-the art Moses system along with the Giza + + toolkit, as well as the IRSTLM language modeling toolkit, as proposed in the Moses’ scripts. The summarized …

Machine learning based optimized pruning approach for decoding in statistical machine translation
D Banik, A Ekbal, P Bhattacharyya – IEEE Access, 2018 – ieeexplore.ieee.org
Page 1. Received November 7, 2018, accepted November 22, 2018, date of publication December 25, 2018, date of current version January 7, 2019. Digital Object Identifier 10.1109/ACCESS.2018.2883738 Machine Learning Based Optimized Pruning …

Morpheme-Based Bi-Directional Ge’ez-Amharic Machine Translation
T Kassa – 2018 – 213.55.95.56
… MGIZA++ for alignment of word and morpheme, morfessor and rules were used for morphological segmentation and IRSTLM for language modeling. After preparing and designing the prototype and the … FVSO – Verb- Subject-Object IRSTLM –Institute of Research …

English to Bodo Machine Transliteration System for Statistical Machine Translation
S Islam, BS Purkayastha – International Journal of Applied …, 2018 – ripublication.com
… Language Model: The Language Model (LM) has been built using KenLM and IRSTLM toolkits to compute the probability of the Bodo sentences. The LM is used to ensure the fluency of the translated Bodo sentences in the system …

Digital Automatic Speech Recognition using Kaldi
S Alyousefi – 2018 – repository.lib.fit.edu
Page 1. Digital Automatic Speech Recognition using Kaldi By Sarah Habeeb Alyousefi Bachelor of Science Computer and software Engineering Al-Mustansiriya University College of Engineering A thesis submitted to the College of Engineering at Florida Institute of Technology …

Informative quality estimation of machine translation output
A Tezcan – 2018 – core.ac.uk
Page 1. Promotor Prof. dr. Lieve Macken Vakgroep Vertalen, tolken en communicatie Copromotor Prof. dr. Véronique Hoste Vakgroep Vertalen, tolken en communicatie Decaan Prof. dr. Marc Boone Rector Prof. dr. Rik Van de Walle Page 2. Informative Quality Estimation of …

A Systematic Review of Automated Grammar Checking in English Language
M Soni, JS Thakur – arXiv preprint arXiv:1804.00540, 2018 – arxiv.org
… 16. Schematic Diagram of Hybrid System[6] The SMT system is developed using best performing tools like Pialign for word alignment, IRSTLM to build target language model and Moses for decoding. The system is able to achieve best values for precision, recall and F-score …

Reliable training scenarios for dealing with minimal parallel-resource language pairs in statistical machine translation
B Ahmadniaye Bosari – 2018 – ddd.uab.cat
Page 1. ADVERTIMENT. L?accés als continguts d?aquesta tesi queda condicionat a l?acceptació de les condicions d?ús establertes per la següent llicència Creative Commons: http://cat.creativecommons.org/?page_id=184 ADVERTENCIA …

Creating a strong statistical machine translation system by combining different decoders
A ElMaghraby – 2018 – dar.aucegypt.edu
Page 1. The American University in Cairo School of Sciences and Engineering Creating a Strong Statistical Machine Translation System by Combining Different Decoders A Thesis Submitted to the Department of Computer Science and …

English-Wolaytta Machine Translation Using Statistical Approach
M MARA – 2018 – repository.smuc.edu.et

Characterizing Sequence to Sequence Models
L Shekhar – 2018 – search.proquest.com
Page 1. Characterizing Sequence to Sequence Models A Thesis presented by Leena Shekhar to The Graduate School in Partial Fulfillment of the Requirements for the Degree of Master of Science in Computer Science Stony Brook University May 2018 Page 2 …