Papers by Peter Polák
Robustness of Multi-Source MT to Transcription Errors (2023.findings-acl)
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| Challenge: | In multilingual settings, the same content may be available in various languages via simultaneous interpreting, dubbing or subtitling. |
| Approach: | They hypothesize that leveraging multiple sources will improve translation quality if the sources complement one another in terms of correct information they contain. |
| Outcome: | The proposed method is robust to speech recognition errors on a 10-hour ESIC corpus. |
ELITR Multilingual Live Subtitling: Demo and Strategy (2021.eacl-demos)
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Ondřej Bojar, Dominik Macháček, Sangeet Sagar, Otakar Smrž, Jonáš Kratochvíl, Peter Polák, Ebrahim Ansari, Mohammad Mahmoudi, Rishu Kumar, Dario Franceschini, Chiara Canton, Ivan Simonini, Thai-Son Nguyen, Felix Schneider, Sebastian Stüker, Alex Waibel, Barry Haddow, Rico Sennrich, Philip Williams
| Challenge: | Using a prototype, we present an automatic speech translation system for live subtitling of conference speech . the system is routinely tested in recognizing English, Czech, and German speech - and presenting it simultaneously into 42 target languages. |
| Approach: | They propose an automatic speech translation system aimed at live subtitling of conference presentations. |
| Outcome: | The proposed system is a working prototype that is routinely tested in recognizing English, Czech, and German speech and presenting it translated simultaneously into 42 target languages. |
Large Corpus of Czech Parliament Plenary Hearings (2020.lrec-1)
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| Challenge: | a corpus of Czech parliament plenary sessions is a valuable resource for future research . only a few public datasets are available in the Czech language . end-to-end approaches require extensive training data to produce competitive results . |
| Approach: | They present a corpus of Czech parliament plenary sessions which is a large corpus . they combine a traditional approach with a more traditional approach . |
| Outcome: | The proposed model architectures can be used to train and evaluate speech recognition systems on a large corpus of speech data and transcripts. |
Evaluating the IWSLT2023 Speech Translation Tasks: Human Annotations, Automatic Metrics, and Segmentation (2024.lrec-main)
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Matthias Sperber, Ondřej Bojar, Barry Haddow, Dávid Javorský, Xutai Ma, Matteo Negri, Jan Niehues, Peter Polák, Elizabeth Salesky, Katsuhito Sudoh, Marco Turchi
| Challenge: | a meta-analysis of human evaluation for speech translation has not been conducted . noisy data and segmentation mismatches are challenges for automatic metrics . |
| Approach: | They propose an evaluation strategy based on automatic resegmentation and direct assessment with segment context. |
| Outcome: | The proposed evaluation strategy is robust and scores well-correlated with other types of human judgements. |
ESPnet-ST-v2: Multipurpose Spoken Language Translation Toolkit (2023.acl-demo)
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Brian Yan, Jiatong Shi, Yun Tang, Hirofumi Inaguma, Yifan Peng, Siddharth Dalmia, Peter Polák, Patrick Fernandes, Dan Berrebbi, Tomoki Hayashi, Xiaohui Zhang, Zhaoheng Ni, Moto Hira, Soumi Maiti, Juan Pino, Shinji Watanabe
| Challenge: | ESPnet-ST-v2 is a revamp of the open-source spoken language translation toolkit . it supports offline speech-to-text translation (ST), simultaneous speech- to-text (SST), and offline speech to-speech (S2ST) |
| Approach: | They propose to revamp the open-source ESPnet-ST toolkit to support offline speech-to-text translation, simultaneous speech- to-text and offline speech to-speech translation. |
| Outcome: | The updated version of ESPnet-ST supports offline speech-to-text translation (ST), simultaneous speech- to-text (SST), and offline speech to-speech translation (S2ST). |
ALIGNMEET: A Comprehensive Tool for Meeting Annotation, Alignment, and Evaluation (2022.lrec-1)
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| Challenge: | Summarization is a challenging problem, and it is difficult to create, correct, and evaluate the summaries manually. |
| Approach: | They propose an open-source tool for meeting annotation, alignment, and evaluation . the tool aims to provide an efficient and clear interface for fast annotation . |
| Outcome: | The proposed tool is open-source and installable from PyPI. |
The Green KNIGHT: Green Machine Translation with Knowledge-Distilled, Narrow, Inexpensive, Greedy, Hybrid Transformers (2025.findings-emnlp)
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| Challenge: | State-of-the-art neural machine translation models deliver high-quality translations at the expense of high inference latency and energy consumption. |
| Approach: | They propose a hardware-agnostic collection of recipes to optimize translation speed and energy consumption. |
| Outcome: | The Green KNIGHT optimizes translation speed and energy consumption with a moderate trade-off in quality. |