Spoken Language Translation for Polish
Krzysztof Marasek, {\L}ukasz Brocki, Danijel Korzinek, Krzysztof, Wo{\l}k, Ryszard Gubrynowicz

TL;DR
This paper discusses advancements in spoken language translation for Polish, focusing on ASR adaptation, language modeling, and statistical translation techniques, with promising results in specific domains and ongoing challenges in less defined areas.
Contribution
It presents novel adaptations of ASR and MT models for Polish, integrating recent deep learning techniques and domain-specific data to improve translation quality.
Findings
Encouraging results in travel, parliamentary, medical, and movie domains
Progress in Polish ASR with state-of-the-art models
Ongoing challenges in less defined domains like lectures and presentations
Abstract
Spoken language translation (SLT) is becoming more important in the increasingly globalized world, both from a social and economic point of view. It is one of the major challenges for automatic speech recognition (ASR) and machine translation (MT), driving intense research activities in these areas. While past research in SLT, due to technology limitations, dealt mostly with speech recorded under controlled conditions, today's major challenge is the translation of spoken language as it can be found in real life. Considered application scenarios range from portable translators for tourists, lectures and presentations translation, to broadcast news and shows with live captioning. We would like to present PJIIT's experiences in the SLT gained from the Eu-Bridge 7th framework project and the U-Star consortium activities for the Polish/English language pair. Presented research concentrates…
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Taxonomy
TopicsNatural Language Processing Techniques · Speech Recognition and Synthesis · Topic Modeling
