Reusing Latent Speech Representations for Query-Conditioned Topic Localization in Transcripts
Paper recorded by Signals 4 on 2026-09-18 in cs.CL. Abstract reproduced from arXiv; link to the original below.
Published 2026-09-18 on arXiv · recorded by Signals 4 on 2026-09-21
Category: cs.CL · 自然语言处理 · first seen 2026-09-21
Abstract
Long transcripts are costly inputs for downstream NLP systems and often contain irrelevant context. We study query-conditioned topic localization: predicting the sentence span in a transcript that best addresses a topic-title query. To improve span localization, we reuse ASR encoder states as sentence-level representations and fuse them with textual embeddings. This lets lightweight span locators
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Cite this page: Reusing Latent Speech Representations for Query-Conditioned Topic Localization in Transcripts: the #7 most recent of 200 cs.CL papers we have recorded (as of 2026-09-18). Source: Signals 4 (Signals API) — https://data.jiangzhang.ca/signals4/t/papers/reusing-latent-speech-representations-for-query-conditioned-topic-localization-i.html
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