NineOneOne: Exploratory Research on Recognizing Non-English Speech for Emergency Triage in Disaster Response

这项探索性的研究旨在证明，自动语音识别（ASR）和机器翻译（MT）的新方法能够很好地实现自动、实时翻译，以满足紧急分诊的需要。 在任何重大灾难中，比如飓风，都会在短时间内接到大量的9-1-1紧急电话，其中许多电话是用英语以外的语言打的。 即使在最好的情况下，美国许多9 - 1 - 1中心也长期缺乏对非英语呼叫进行分类的翻译。对于紧急情况分类，完全识别和翻译是不必要的;只需要识别紧急情况的类型和相关细节，如位置。然而，需要新的高级ASR方法来处理非英语9 - 1 - 1呼叫的困难特征，这些呼叫在嘈杂的环境中包含情绪困扰的语音，并且可能包括与其他语言混合的英语短语。对于ASR，探索性系统使用由发音特征增强的多语言声学模型，以及与n-gram语言模型相结合的多语言语法来识别语音。至于MT，探索性系统仅将ASR输出分类为“域”，即与诸如“请求救护车”或“报告洪水”之类的分类相关的类别。 探索性的系统适用于西班牙语，但所使用的方法适用于任何语言，并可转移到其他任务领域。证明语音翻译技术为9 - 1 - 1呼叫中心服务的可行性应该使后续项目能够在重大灾难中更好地为所有非英语国家的人服务。 我们期望使所得到的转录和注释的语音语料库提供给其他研究人员。

This exploratory research seeks to demonstrate that new approaches toAutomatic Speech Recognition (ASR) and Machine Translation (MT) permitautomatic, real-time translation well enough for emergency triage. Inany major disaster, such as a hurricane, there will be a huge numberof 9-1-1 emergency calls in a short period of time; many will be inlanguages other than English. Even in the best of times, there is achronic shortage of translation for triage of non-English calls atmany U.S. 9-1-1 centers.For emergency triage, full recognition and translation areunnecessary; only the type of emergency and relevant details, such aslocation, need be recognized. Nevertheless, new advanced ASR methodsare needed to handle the difficult characteristics of non-English9-1-1 calls, which contain emotionally-distressed speech in noisyenvironments and may include English phrases mixed in with the otherlanguage. For ASR, the exploratory system uses multilingual acousticmodels enhanced by articulatory features, and multilingual grammarscombined with n-gram language models, to recognize speech. As for MT,the exploratory system only classifies the ASR outputs into ``DomainActions'', categories relevant to triage such as ``Request-Ambulance''or ``Report-Flooding''. The exploratory system works with Spanish,but the approaches used are applicable to any language, andtransferable to other task domains.Demonstrating the feasibility of speech translation technology forserving 9-1-1 call centers should enable follow-on projects to betterserve all non-English speakers during major disasters. We expect tomake the resulting transcribed and annotated speech corpus availablefor other researchers.