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Speech Translation by Confusion Network Decoding

Nicola Bertoldi, Richard Zens, Marcello Federico
2007 2007 IEEE International Conference on Acoustics, Speech and Signal Processing - ICASSP '07  
Experimental results in terms of decoding speed and translation accuracy are reported on a real-data task, namely the translation of Plenary Speeches at the European Parliament from Spanish to English.  ...  The confusion network decoder results as an extension of a state-of-the-art phrase-based text translation system.  ...  CONCLUSIONS This work presented a new implementation of a phrase-based decoder for speech translation.  ... 
doi:10.1109/icassp.2007.367315 dblp:conf/icassp/BertoldiZF07 fatcat:4mpl5jj3m5bhvkqafg3ej2i4oi

Text Segmentation Criteria for Statistical Machine Translation [chapter]

Mauro Cettolo, Marcello Federico
2006 Lecture Notes in Computer Science  
In particular, in statistical machine translation, heuristic search algorithms are employed whose level of approximation depends on the length of the input.  ...  In this work, we investigate several text segmentation criteria and verify their impact on translation performance by means of a statistical phrase-based translation system.  ...  Acknowledgments This work has been funded by the European Union under the integrated project TC-STAR -Technology and Corpora for Speech to Speech Translation -(IST-2002-FP6-506738, http://www.tc-star.org  ... 
doi:10.1007/11816508_66 fatcat:llcs2meokfestdhnrynkjxrul4

Neural Machine Translation from English to Hindi

Aditya Mittal
2020 International Journal for Research in Applied Science and Engineering Technology  
Keywords: Neural machine translation, long and short term memory, algorithm, encoder decoder model. I.  ...  Statistical Machine Translation is solving the problem of machine translation but it requires huge data sets and performs well on similar grammar structured language pairs.  ...  Now we create 3 numpy arrays and encoder for input, decoder for input and decoder for target. We will use this for indexing each word.  ... 
doi:10.22214/ijraset.2020.5494 fatcat:s4g7k3fmfvg4jplcjwxnh3meo4

Incremental translation using hierarchichal phrase-based translation system

Maryam Siahbani, Ramtin Mehdizadeh Seraj, Baskaran Sankaran, Anoop Sarkar
2014 2014 IEEE Spoken Language Technology Workshop (SLT)  
Leftto-right (LR) decoding [2] is a promising decoding algorithm for Hiero that produces the output translation in left to right order.  ...  But Hiero typically uses the CKY decoding algorithm which requires the entire input sentence before decoding begins, as it produces the translation in a bottom-up fashion.  ...  Thanks to the anonymous reviewers for their comments.  ... 
doi:10.1109/slt.2014.7078552 dblp:conf/slt/SiahbaniSSS14 fatcat:ppuccnbp5vddhcphju4y6lkysy

Classification of Analyzed Text in Speech Recognition Using RNN-LSTM in Comparison with Convolutional Neural Network to Improve Precision for Identification of Keywords

Bathaloori Reddy Prasad
2021 Revista GEINTEC  
Aim: Text classification is a method to classify the features from language translation in speech recognition from English to Telugu using a recurrent neural network- long short term memory (RNN-LSTM)  ...  algorithm RNN implies speech recognition that can be compared with convolutional is the second technique.  ...  Funding We thank the following organizations for providing financial support that enabled us to complete the study.  ... 
doi:10.47059/revistageintec.v11i2.1739 fatcat:4mkgwmtf3fhmnhwzqz2muhn3sa

Page 101 of Computational Linguistics Vol. 29, Issue 1 [page]

2003 Computational Linguistics  
Tillmann and Ney DP Beam Search for Statistical MT 2.2 Search Algorithms for Statistical Machine Translation In this section, we give a short overview of search procedures used in statistical MT: Brown  ...  Wang and Waibel (1997) presents a search algorithm for the IBM-2 translation model based on the A* concept and multiple stacks.  ... 

T.U.E.S.D.A.Y (Translation Using machine learning from English Speech to Devanagari Automated for You)

Varun Soni, Rizwan Shaikh, Sayantan Mahato, Shaikh Phiroj
2021 International Journal of Computer Applications  
(Translation Using machine learning for English Speech to Devanagari Automated for You) and is divided into three conversion modules: English speech to English text, English text to Devanagari text, and  ...  With these issues in mind, this group is trying to build an automatic voice dubbing system: a speech-to-speech translation pipeline which can help users easily understand other users without the worry  ...  The extracted audio from the video is fed to a deep speech model which is mainly composed of an Acoustic model and decoder. The decoder uses a beam search algorithm to output textual transcript.  ... 
doi:10.5120/ijca2021921387 fatcat:sr2e7euqczhffd25ga5fg2zoi4

A Survey of Voice Translation Methodologies - Acoustic Dialect Decoder [article]

Hans Krupakar, Keerthika Rajvel, Bharathi B, Angel Deborah S, Vallidevi Krishnamurthy
2016 arXiv   pre-print
Speech Translation has always been about giving source text or audio input and waiting for system to give translated output in desired form.  ...  In this paper, we present the Acoustic Dialect Decoder (ADD) - a voice to voice ear-piece translation device.  ...  synthesize speech waveform corresponding to the text input [35] , [36] .HTS technology is preferred because it overcomes the drawbacks of Formant and Articulatory synthesis as HMM based is a statistical  ... 
arXiv:1610.03934v1 fatcat:3jgucadf6jcirnpygijtfew4ai

Multilingual Spoken Language Understanding using graphs and multiple translations

Marcos Calvo, Lluís-Felip Hurtado, Fernando Garcia, Emilio Sanchis, Encarna Segarra
2016 Computer Speech and Language  
We also propose an algorithm to parse graphs of words with the statistical semantic model.  ...  The experimental results confirm the good behavior of this approach using French and English as input languages in a spoken language understanding task that was developed for Spanish.  ...  For our semantic decoding algorithm, we have represented these LMs as stochastic finite state automata.  ... 
doi:10.1016/j.csl.2016.01.002 fatcat:x5ejm4avm5hrfndlbswehbju7m

Efficient Phrase-Table Representation for Machine Translation with Applications to Online MT and Speech Translation

Richard Zens, Hermann Ney
2007 North American Chapter of the Association for Computational Linguistics  
This algorithm enables the use of significantly larger input word graphs in a more efficient way resulting in improved translation quality.  ...  One problem in speech translation is the matching of phrases in the input word graph and the phrase-table.  ...  Additionally, we would like to thank all group members of the JHU 2006 summer research workshop Open Source Toolkit for Statistical Machine Translation.  ... 
dblp:conf/naacl/ZensN07 fatcat:5cjvmzuwanbtjb4ru7dzqmwobm

Multiple Translation-Engine-based Hypotheses and Edit-Distance-based Rescoring for a Greedy Decoder for Statistical Machine Translation

Michael Paul, Eiichiro Sumita, Seiichi Yamamoto
2005 IPSJ Digital Courier  
This paper extends a greedy decoder for statistical machine translation (SMT), which searches for an optimal translation by using SMT models starting from a decoder seed, i.e., the source language input  ...  Second, a rescoring method based on the edit-distance between the initial translation hypothesis and the outputs of the decoder is used to compensate for problems of conventional greedy decoding solely  ...  In other words, MAD is the target of our speech-to-speech translation system and BTEC is used as a resource to acquire translation knowledge for the translation system.  ... 
doi:10.2197/ipsjdc.1.561 fatcat:y7bhwaii5zhbfjty7h2pfzwgge

Decoding algorithm in statistical machine translation

Ye-Yi Wang, Alex Waibel
1997 Proceedings of the 35th annual meeting on Association for Computational Linguistics -  
Decoding algorithm is a crucial part in statistical machine translation. We describe a stack decoding algorithm in this paper.  ...  We evaluate and compare these techniques/models in our statistical machine translation system.  ...  Acknowledgements We would like to thank John Lafferty for enlightening discussions on this work. We would also like to thank the anonymous ACL reviewers for valuable comments.  ... 
doi:10.3115/976909.979664 dblp:conf/acl/WangW97 fatcat:ghxk2grhdfejrn7j2tczufldzi

The 2020 ESPnet update: new features, broadened applications, performance improvements, and future plans [article]

Shinji Watanabe, Florian Boyer, Xuankai Chang, Pengcheng Guo, Tomoki Hayashi, Yosuke Higuchi, Takaaki Hori, Wen-Chin Huang, Hirofumi Inaguma, Naoyuki Kamo, Shigeki Karita, Chenda Li (+3 others)
2020 arXiv   pre-print
Now ESPnet also includes text to speech (TTS), voice conversation (VC), speech translation (ST), and speech enhancement (SE) with support for beamforming, speech separation, denoising, and dereverberation  ...  The project has grown rapidly and now covers a wide range of speech processing applications.  ...  for a given input utterance using an encoderdecoder (RNN, Transformer, etc.), CTC and a language model (LM) [22] .  ... 
arXiv:2012.13006v1 fatcat:zvvoohohdzesbh2t4b626xj3dq

Incremental Segmentation and Decoding Strategies for Simultaneous Translation

Mahsa Yarmohammadi, Vivek Kumar Rangarajan Sridhar, Srinivas Bangalore, Baskaran Sankaran
2013 International Joint Conference on Natural Language Processing  
We compare and contrast three incremental decoding and two different input segmentation strategies, including our proposed method, for simultaneous translation.  ...  Simultaneous translation is the challenging task of listening to source language speech, and at the same time, producing target language speech.  ...  Acknowledgments We would like to thank Brian Roark for his valuable discussions.  ... 
dblp:conf/ijcnlp/YarmohammadiSBS13 fatcat:tg5mkvkrgfdspfvchod4msoxoy

ON-TRAC Consortium for End-to-End and Simultaneous Speech Translation Challenge Tasks at IWSLT 2020 [article]

Maha Elbayad, Ha Nguyen, Fethi Bougares, Natalia Tomashenko, Antoine Caubrière, Benjamin Lecouteux, Yannick Estève, Laurent Besacier
2020 arXiv   pre-print
For speech-to-text simultaneous translation, we attach a wait-k MT system to a hybrid ASR system.  ...  Attention-based encoder-decoder models, trained end-to-end, were used for our submissions to the offline speech translation track.  ...  ., 2019) Algorithm 1 ASR+MT decoding algorithm Input: source audio blocks x. Output: translation hypothesis y.  ... 
arXiv:2005.11861v1 fatcat:a6l5yzfmyfghbik64ajjfu5w5e
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