Search Results for author: Elizabeth Salesky

Found 33 papers, 6 papers with code

A surprisal–duration trade-off across and within the world’s languages

1 code implementation EMNLP 2021 Tiago Pimentel, Clara Meister, Elizabeth Salesky, Simone Teufel, Damián Blasi, Ryan Cotterell

We thus conclude that there is strong evidence of a surprisal–duration trade-off in operation, both across and within the world’s languages.

FINDINGS OF THE IWSLT 2021 EVALUATION CAMPAIGN

no code implementations ACL (IWSLT) 2021 Antonios Anastasopoulos, Ondřej Bojar, Jacob Bremerman, Roldano Cattoni, Maha Elbayad, Marcello Federico, Xutai Ma, Satoshi Nakamura, Matteo Negri, Jan Niehues, Juan Pino, Elizabeth Salesky, Sebastian Stüker, Katsuhito Sudoh, Marco Turchi, Alexander Waibel, Changhan Wang, Matthew Wiesner

The evaluation campaign of the International Conference on Spoken Language Translation (IWSLT 2021) featured this year four shared tasks: (i) Simultaneous speech translation, (ii) Offline speech translation, (iii) Multilingual speech translation, (iv) Low-resource speech translation.

Translation

Findings of the IWSLT 2022 Evaluation Campaign

no code implementations IWSLT (ACL) 2022 Antonios Anastasopoulos, Loïc Barrault, Luisa Bentivogli, Marcely Zanon Boito, Ondřej Bojar, Roldano Cattoni, Anna Currey, Georgiana Dinu, Kevin Duh, Maha Elbayad, Clara Emmanuel, Yannick Estève, Marcello Federico, Christian Federmann, Souhir Gahbiche, Hongyu Gong, Roman Grundkiewicz, Barry Haddow, Benjamin Hsu, Dávid Javorský, Vĕra Kloudová, Surafel Lakew, Xutai Ma, Prashant Mathur, Paul McNamee, Kenton Murray, Maria Nǎdejde, Satoshi Nakamura, Matteo Negri, Jan Niehues, Xing Niu, John Ortega, Juan Pino, Elizabeth Salesky, Jiatong Shi, Matthias Sperber, Sebastian Stüker, Katsuhito Sudoh, Marco Turchi, Yogesh Virkar, Alexander Waibel, Changhan Wang, Shinji Watanabe

The evaluation campaign of the 19th International Conference on Spoken Language Translation featured eight shared tasks: (i) Simultaneous speech translation, (ii) Offline speech translation, (iii) Speech to speech translation, (iv) Low-resource speech translation, (v) Multilingual speech translation, (vi) Dialect speech translation, (vii) Formality control for speech translation, (viii) Isometric speech translation.

Speech-to-Speech Translation Translation

KIT’s Multilingual Neural Machine Translation systems for IWSLT 2017

no code implementations IWSLT 2017 Ngoc-Quan Pham, Matthias Sperber, Elizabeth Salesky, Thanh-Le Ha, Jan Niehues, Alexander Waibel

For the SLT track, in addition to a monolingual neural translation system used to generate correct punctuations and true cases of the data prior to training our multilingual system, we introduced a noise model in order to make our system more robust.

Machine Translation Translation

The IWSLT 2019 Evaluation Campaign

no code implementations EMNLP (IWSLT) 2019 Jan Niehues, Rolando Cattoni, Sebastian Stüker, Matteo Negri, Marco Turchi, Thanh-Le Ha, Elizabeth Salesky, Ramon Sanabria, Loic Barrault, Lucia Specia, Marcello Federico

The IWSLT 2019 evaluation campaign featured three tasks: speech translation of (i) TED talks and (ii) How2 instructional videos from English into German and Portuguese, and (iii) text translation of TED talks from English into Czech.

Translation

UniMorph 4.0: Universal Morphology

no code implementations7 May 2022 Khuyagbaatar Batsuren, Omer Goldman, Salam Khalifa, Nizar Habash, Witold Kieraś, Gábor Bella, Brian Leonard, Garrett Nicolai, Kyle Gorman, Yustinus Ghanggo Ate, Maria Ryskina, Sabrina J. Mielke, Elena Budianskaya, Charbel El-Khaissi, Tiago Pimentel, Michael Gasser, William Lane, Mohit Raj, Matt Coler, Jaime Rafael Montoya Samame, Delio Siticonatzi Camaiteri, Benoît Sagot, Esaú Zumaeta Rojas, Didier López Francis, Arturo Oncevay, Juan López Bautista, Gema Celeste Silva Villegas, Lucas Torroba Hennigen, Adam Ek, David Guriel, Peter Dirix, Jean-Philippe Bernardy, Andrey Scherbakov, Aziyana Bayyr-ool, Antonios Anastasopoulos, Roberto Zariquiey, Karina Sheifer, Sofya Ganieva, Hilaria Cruz, Ritván Karahóǧa, Stella Markantonatou, George Pavlidis, Matvey Plugaryov, Elena Klyachko, Ali Salehi, Candy Angulo, Jatayu Baxi, Andrew Krizhanovsky, Natalia Krizhanovskaya, Elizabeth Salesky, Clara Vania, Sardana Ivanova, Jennifer White, Rowan Hall Maudslay, Josef Valvoda, Ran Zmigrod, Paula Czarnowska, Irene Nikkarinen, Aelita Salchak, Brijesh Bhatt, Christopher Straughn, Zoey Liu, Jonathan North Washington, Yuval Pinter, Duygu Ataman, Marcin Wolinski, Totok Suhardijanto, Anna Yablonskaya, Niklas Stoehr, Hossep Dolatian, Zahroh Nuriah, Shyam Ratan, Francis M. Tyers, Edoardo M. Ponti, Grant Aiton, Aryaman Arora, Richard J. Hatcher, Ritesh Kumar, Jeremiah Young, Daria Rodionova, Anastasia Yemelina, Taras Andrushko, Igor Marchenko, Polina Mashkovtseva, Alexandra Serova, Emily Prud'hommeaux, Maria Nepomniashchaya, Fausto Giunchiglia, Eleanor Chodroff, Mans Hulden, Miikka Silfverberg, Arya D. McCarthy, David Yarowsky, Ryan Cotterell, Reut Tsarfaty, Ekaterina Vylomova

The project comprises two major thrusts: a language-independent feature schema for rich morphological annotation and a type-level resource of annotated data in diverse languages realizing that schema.

Morphological Inflection

Assessing Evaluation Metrics for Speech-to-Speech Translation

no code implementations26 Oct 2021 Elizabeth Salesky, Julian Mäder, Severin Klinger

Speech-to-speech translation combines machine translation with speech synthesis, introducing evaluation challenges not present in either task alone.

Machine Translation Speech Synthesis +2

A surprisal--duration trade-off across and within the world's languages

1 code implementation30 Sep 2021 Tiago Pimentel, Clara Meister, Elizabeth Salesky, Simone Teufel, Damián Blasi, Ryan Cotterell

We thus conclude that there is strong evidence of a surprisal--duration trade-off in operation, both across and within the world's languages.

Robust Open-Vocabulary Translation from Visual Text Representations

1 code implementation EMNLP 2021 Elizabeth Salesky, David Etter, Matt Post

Machine translation models have discrete vocabularies and commonly use subword segmentation techniques to achieve an 'open vocabulary.'

Machine Translation Translation

Tutorial Proposal: End-to-End Speech Translation

no code implementations EACL 2021 Jan Niehues, Elizabeth Salesky, Marco Turchi, Matteo Negri

Speech translation is the translation of speech in one language typically to text in another, traditionally accomplished through a combination of automatic speech recognition and machine translation.

Automatic Speech Recognition Machine Translation +2

The Multilingual TEDx Corpus for Speech Recognition and Translation

no code implementations2 Feb 2021 Elizabeth Salesky, Matthew Wiesner, Jacob Bremerman, Roldano Cattoni, Matteo Negri, Marco Turchi, Douglas W. Oard, Matt Post

We present the Multilingual TEDx corpus, built to support speech recognition (ASR) and speech translation (ST) research across many non-English source languages.

speech-recognition Speech Recognition +1

FINDINGS OF THE IWSLT 2020 EVALUATION CAMPAIGN

no code implementations WS 2020 Ebrahim Ansari, Amittai Axelrod, Nguyen Bach, Ond{\v{r}}ej Bojar, Roldano Cattoni, Fahim Dalvi, Nadir Durrani, Marcello Federico, Christian Federmann, Jiatao Gu, Fei Huang, Kevin Knight, Xutai Ma, Ajay Nagesh, Matteo Negri, Jan Niehues, Juan Pino, Elizabeth Salesky, Xing Shi, Sebastian St{\"u}ker, Marco Turchi, Alex Waibel, er, Changhan Wang

The evaluation campaign of the International Conference on Spoken Language Translation (IWSLT 2020) featured this year six challenge tracks: (i) Simultaneous speech translation, (ii) Video speech translation, (iii) Offline speech translation, (iv) Conversational speech translation, (v) Open domain translation, and (vi) Non-native speech translation.

Translation

A Corpus for Large-Scale Phonetic Typology

no code implementations ACL 2020 Elizabeth Salesky, Eleanor Chodroff, Tiago Pimentel, Matthew Wiesner, Ryan Cotterell, Alan W. black, Jason Eisner

A major hurdle in data-driven research on typology is having sufficient data in many languages to draw meaningful conclusions.

Phone Features Improve Speech Translation

1 code implementation ACL 2020 Elizabeth Salesky, Alan W. black

End-to-end models for speech translation (ST) more tightly couple speech recognition (ASR) and machine translation (MT) than a traditional cascade of separate ASR and MT models, with simpler model architectures and the potential for reduced error propagation.

Machine Translation speech-recognition +2

Relative Positional Encoding for Speech Recognition and Direct Translation

no code implementations20 May 2020 Ngoc-Quan Pham, Thanh-Le Ha, Tuan-Nam Nguyen, Thai-Son Nguyen, Elizabeth Salesky, Sebastian Stueker, Jan Niehues, Alexander Waibel

We also show that this model is able to better utilize synthetic data than the Transformer, and adapts better to variable sentence segmentation quality for speech translation.

Sentence segmentation speech-recognition +2

Generalized Entropy Regularization or: There's Nothing Special about Label Smoothing

no code implementations ACL 2020 Clara Meister, Elizabeth Salesky, Ryan Cotterell

Prior work has explored directly regularizing the output distributions of probabilistic models to alleviate peaky (i. e. over-confident) predictions, a common sign of overfitting.

Text Generation

Exploring Phoneme-Level Speech Representations for End-to-End Speech Translation

no code implementations ACL 2019 Elizabeth Salesky, Matthias Sperber, Alan W. black

Previous work on end-to-end translation from speech has primarily used frame-level features as speech representations, which creates longer, sparser sequences than text.

Translation

Fluent Translations from Disfluent Speech in End-to-End Speech Translation

no code implementations NAACL 2019 Elizabeth Salesky, Matthias Sperber, Alex Waibel

Spoken language translation applications for speech suffer due to conversational speech phenomena, particularly the presence of disfluencies.

Machine Translation speech-recognition +2

Optimizing Segmentation Granularity for Neural Machine Translation

no code implementations19 Oct 2018 Elizabeth Salesky, Andrew Runge, Alex Coda, Jan Niehues, Graham Neubig

However, the granularity of these subword units is a hyperparameter to be tuned for each language and task, using methods such as grid search.

Machine Translation Translation

Operational Assessment of Keyword Search on Oral History

no code implementations LREC 2016 Elizabeth Salesky, Jessica Ray, Wade Shen

This project assesses the resources necessary to make oral history searchable by means of automatic speech recognition (ASR).

Automatic Speech Recognition Information Retrieval +1

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