Summary of Resolving Transcription Ambiguity in Spanish: a Hybrid Acoustic-lexical System For Punctuation Restoration, by Xiliang Zhu et al.
Resolving Transcription Ambiguity in Spanish: A Hybrid Acoustic-Lexical System for Punctuation Restoration
by Xiliang Zhu, Chia-Tien Chang, Shayna Gardiner, David Rossouw, Jonas Robertson
First submitted to arxiv on: 5 Feb 2024
Categories
- Main: Computation and Language (cs.CL)
- Secondary: Artificial Intelligence (cs.AI)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary The proposed hybrid acoustic-lexical punctuation restoration system for Spanish transcription addresses the limitations of conventional lexical-based approaches by consolidating acoustic and lexical signals through a modular process. This novel method improves F1 scores of question marks and overall punctuation restoration on both public and internal Spanish conversational datasets, outperforming Large Language Models (LLMs) in accuracy, reliability, and latency. Furthermore, the system’s integration with an Automatic Speech Recognition (ASR) module also benefits the ASR model’s Word Error Rate (WER). |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary Punctuation is important for making transcripts easy to read. After speech recognition systems convert spoken words into text, punctuation helps make sense of what was said. However, it can be tricky to add punctuation correctly, especially in languages like Spanish where there are many different ways to ask a question or make a statement without punctuation. Researchers have developed a new system that uses both the sound and meaning of words to add punctuation correctly. This system is better than others at adding question marks and punctuation overall. It’s also faster and more reliable. |
