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        <title>Selected-Layer Codec Compression for Compact Speech Translation Models: An IWSLT 2026 English-to-Chinese Submission</title>
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            <title>Proceedings of the 23rd International Conference on Spoken Language Translation (IWSLT 2026)</title>
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        <name type="personal">
            <namePart type="given">Elizabeth</namePart>
            <namePart type="family">Salesky</namePart>
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                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
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        <name type="personal">
            <namePart type="given">Antonios</namePart>
            <namePart type="family">Anastasopoulos</namePart>
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                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
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        <name type="personal">
            <namePart type="given">Matteo</namePart>
            <namePart type="family">Negri</namePart>
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        <name type="personal">
            <namePart type="given">Marcello</namePart>
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    <abstract>This paper describes a selected-layer codec compression approach submitted to the IWSLT 2026 Model Compression Shared Task for constrained English-to-Chinese speech translation. The approach is compared against standard quantization, global codec compression, and a pruning-plus-codec variant. The results indicate that translation quality after compression depends strongly on where compression is applied. In these experiments, selected-layer compression preserves translation quality better than uniform global compression, with one variant achieving the highest COMET score among compressed systems and another providing the strongest overall quality-compression trade-off among the custom codec methods. These results suggest that simple layer-aware post-hoc compression is a viable approach for model compression in constrained English-to-Chinese speech translation.</abstract>
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%0 Conference Proceedings
%T Selected-Layer Codec Compression for Compact Speech Translation Models: An IWSLT 2026 English-to-Chinese Submission
%A Palomino, Alonso
%Y Salesky, Elizabeth
%Y Anastasopoulos, Antonios
%Y Negri, Matteo
%Y Federico, Marcello
%S Proceedings of the 23rd International Conference on Spoken Language Translation (IWSLT 2026)
%D 2026
%8 July
%I Association for Computational Linguistics
%C San Diego, USA (in-person and online)
%@ 979-8-89176-411-8
%F palomino-2026-selected
%X This paper describes a selected-layer codec compression approach submitted to the IWSLT 2026 Model Compression Shared Task for constrained English-to-Chinese speech translation. The approach is compared against standard quantization, global codec compression, and a pruning-plus-codec variant. The results indicate that translation quality after compression depends strongly on where compression is applied. In these experiments, selected-layer compression preserves translation quality better than uniform global compression, with one variant achieving the highest COMET score among compressed systems and another providing the strongest overall quality-compression trade-off among the custom codec methods. These results suggest that simple layer-aware post-hoc compression is a viable approach for model compression in constrained English-to-Chinese speech translation.
%U https://aclanthology.org/2026.iwslt-1.4/
%P 40-46

Markdown (Informal)

[Selected-Layer Codec Compression for Compact Speech Translation Models: An IWSLT 2026 English-to-Chinese Submission](https://aclanthology.org/2026.iwslt-1.4/) (Palomino, IWSLT 2026)

• Selected-Layer Codec Compression for Compact Speech Translation Models: An IWSLT 2026 English-to-Chinese Submission (Palomino, IWSLT 2026)

ACL

• Alonso Palomino. 2026. Selected-Layer Codec Compression for Compact Speech Translation Models: An IWSLT 2026 English-to-Chinese Submission. In Proceedings of the 23rd International Conference on Spoken Language Translation (IWSLT 2026), pages 40–46, San Diego, USA (in-person and online). Association for Computational Linguistics.