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Conversational English audio annotations
Text Detection
|...
许可协议: CC-BY 4.0

Overview

Named Entity Recognition (NER) has been mostly studied in the context of written text. Specifically, NER is an important step in de-identification (de-ID) of medical records, many of which are recorded conversations between a patient and a doctor. In such recordings, audio spans with personal information should be redacted, similar to the redaction of sensitive character spans in de-ID for written text.

This dataset was used to test the performance of our Audio De-id pipeline in our NAACL 2019 paper 'Audio De-identification: A New Entity Recognition Task We evaluated our pipeline using a random subset of conversations from the Switchboard (LDC2001S13) and Fisher (LDC2004S13) datasets, which consist of English conversations.

数据概要
数据格式
sound,
数据量
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文件大小
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| 数据量 -- | 大小 --
Conversational English audio annotations
Text Detection
许可协议: CC-BY 4.0

Overview

Named Entity Recognition (NER) has been mostly studied in the context of written text. Specifically, NER is an important step in de-identification (de-ID) of medical records, many of which are recorded conversations between a patient and a doctor. In such recordings, audio spans with personal information should be redacted, similar to the redaction of sensitive character spans in de-ID for written text.

This dataset was used to test the performance of our Audio De-id pipeline in our NAACL 2019 paper 'Audio De-identification: A New Entity Recognition Task We evaluated our pipeline using a random subset of conversations from the Switchboard (LDC2001S13) and Fisher (LDC2004S13) datasets, which consist of English conversations.

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