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New end-to-end ITN system achieves real-time processing with language model

By PulseAugur Editorial · [1 sources] ·

Researchers have developed a new end-to-end system for Inverse Text Normalization (ITN) that can process speech recognition outputs in real-time. This system adapts a pretrained text-to-text language model and employs a Read-Tag-Write decoding policy to achieve streaming capabilities. Experiments on Vietnamese datasets demonstrated that the proposed method matches the accuracy of non-streaming baselines and surpasses hybrid approaches while meeting latency requirements. AI

IMPACT Enables real-time formatting of speech recognition outputs, potentially improving user experience in voice-enabled applications.

RANK_REASON The cluster contains a research paper detailing a new method for Inverse Text Normalization. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.CL →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

New end-to-end ITN system achieves real-time processing with language model

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14 / 100
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The cluster contains a research paper detailing a new method for Inverse Text Normalization. [lever_c_demoted from research: ic=1 ai=1.0]
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High
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COVERAGE [1]

  1. arXiv cs.CL TIER_1 English(EN) · Kiet Anh Hoang, Khanh Le, Bao Nguyen, Linh Pham, Dung Vo, Thai Tran, Mai Nguyen, Tri Nguyen, Vu Le ·

    Towards Efficient Simultaneous Inverse Text Normalization with Pretrained Text-to-Text Language Model and Read-Tag-Write Policy

    arXiv:2610.19492v1 Announce Type: new Abstract: Streaming Inverse Text Normalization (ITN) is vital for converting spoken-form outputs from streaming Automatic Speech Recognition into formatted written text. Existing streaming ITN methods rely on hybrid systems combining neural t…

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