Paper

FormalASR: End-to-End Spoken Chinese to Formal Text

Unreadunread

AI summary

arXiv:2605. 19266v1 Announce Type: new Abstract: Automatic speech recognition (ASR) systems are typically optimized for verbatim transcription, which preserves disfluencies, filler words, and informal spoken structures that are often unsuitable for downstream writing-oriented applications.

Reading status

Priority

About this paper

Authors: Wanyi Ning, Yinshang Guo, Haitao Qian, Jiyuan Cheng, Weiyuan Feng, Yufei Zhang
Released: 2026-05-20 (2mo ago)
Topic: Related to current project
Relation to my work: Read next because FormalASR: End-to-End Spoken Chinese to Formal Text overlaps with clean result "LoRA persona trained on <A> alone emits <B> at 23.5% when a co-trained partner learns <A>...<B>, vs 0% control on Qwen2.5-7B-Instruct (MODERATE confidence)", clean result "Leakage rate is a usable signal for recovering trigger-shaped phrases on Gaperon-1125-1B without knowing the hidden trigger itself (MODERATE confidence)", clean result "Language-mismatch LoRA SFT on Qwen2.5-7B leaks the trained completion language into bystander directives the model was never trained on, absent under same-language SFT (LOW confidence)". Matching terms: text, fill, word, rect, line, stage, model. Source: arxiv cs.CL (NLP).
arXiv: 2605.19266

Ask Claude about this paper

Posts a comment with @claude so the runner spins up a Claude Code session scoped to FormalASR: End-to-End Spoken Chinese to Formal Text. Replies appear in the conversation below.

Comments

No comments yet.

Related records

No links yet.