TDT3 Mandarin Audio

Item Name: TDT3 Mandarin Audio
Author(s): David Graff
LDC Catalog No.: LDC2001S95
ISBN: 1-58563-186-8
ISLRN: 553-735-328-637-8
DOI: https://doi.org/10.35111/nkkx-1576
Member Year(s): 2001
DCMI Type(s): Sound
Sample Type: 1-channel pcm
Sample Rate: 16000
Data Source(s): broadcast news
Project(s): TIDES, TDT, GALE, EARS
Application(s): topic detection and tracking, speech recognition
Language(s): Mandarin Chinese
Language ID(s): cmn
License(s): LDC User Agreement for Non-Members
Online Documentation: LDC2001S95 Documents
Licensing Instructions: Subscription & Standard Members, and Non-Members
Citation: Graff, David. TDT3 Mandarin Audio LDC2001S95. Web Download. Philadelphia: Linguistic Data Consortium, 2001.
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Introduction

This publication contains the TDT3 Broadcast News Mandarin Corpus (Audio), produced by the Linguistic Data Consortium (LDC), catalog number LDC2001S95 and ISBN number 1-58563-186-8. The contents of this publication were recorded from various 60-minute, twice daily Mandarin news programs from VOA, amounting to approximately 123 hours of audio. The transcripts of these broadcasts will be published in the TDT3 Mandarin Text and TDT3 Multilanguage Text Corpora.

Data

Topic Detection and Tracking (TDT) refers to automatic techniques for finding topically related material in streams of data such as newswire and broadcast news. The TDT3 corpus was created to support three TDT3 tasks: find topically homogeneous sections (segmentation), detect the occurrence of new events (detection), and track the reoccurrence of old or new events (tracking).

The goal of Topic Detection and Tracking - Phase 3 (TDT3) is to create core technology to monitor multiple streams of news in multiple languages and media (newswire, radio, television, web sites or some future combination or innovation), segmenting the streams into individual stories, detecting new topics and tracking all stories discussing them. In additional to the TDT-2 tasks of segmentation, detection and tracking, TDT3 adds the tasks of first story detection and story-link detection. The goal of the latter is to detect links between stories that discuss the same topic even though the topic has not been defined in advance.

Please see file.tbl for the directory structure of this publication, as well as a complete list of files.

The data files are recordings of Voice of America (VOA) news broadcasts. The data were collected daily over a period of three months (October-December 1998). The audio files in this corpus are single channel, 16 KHz, 16-bit linear SPHERE files.

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