RATS Speech Activity Detection

Item Name: RATS Speech Activity Detection
Author(s): Kevin Walker, Xiaoyi Ma, David Graff, Stephanie Strassel, Stephanie Sessa, Karen Jones
LDC Catalog No.: LDC2015S02
ISBN: 1-58563-706-8
ISLRN: 648-931-730-249-1
DOI: https://doi.org/10.35111/x1mr-fq11
Release Date: February 16, 2015
Member Year(s): 2015
DCMI Type(s): Sound, Text
Sample Type: pcm
Sample Rate: 16000
Data Source(s): telephone conversations
Project(s): RATS
Application(s): speech activity detection
Language(s): South Levantine Arabic, North Levantine Arabic, English, Persian, Pushto, Urdu
Language ID(s): ajp, apc, eng, fas, pus, urd
License(s): LDC User Agreement for Non-Members
Online Documentation: LDC2015S02 Documents
Licensing Instructions: Subscription & Standard Members, and Non-Members
Citation: Walker, Kevin, et al. RATS Speech Activity Detection LDC2015S02. Web Download. Philadelphia: Linguistic Data Consortium, 2015.
Related Works: View

Introduction

RATS Speech Activity Detection was developed by the Linguistic Data Consortium (LDC) and is comprised of approximately 350 hours of Levantine Arabic, English, Farsi, Pashto, and Urdu conversational telephone speech with automatic and manual annotation of speech segments. The audio was retransmitted over eight channels, making 3,000 hours of total audio. The corpus was created to provide training, development and initial test sets for the Speech Activity Detection (SAD) task in the DARPA RATS (Robust Automatic Transcription of Speech) program.

The goal of the RATS program was to develop human language technology systems capable of performing speech detection, language identification, speaker identification and keyword spotting on the severely degraded audio signals that are typical of various radio communication channels, especially those employing various types of handheld portable transceiver systems. To support that goal, LDC assembled a system for the transmission, reception and digital capture of audio data that allowed a single source audio signal to be distributed and recorded over eight distinct transceiver configurations simultaneously. Those configurations included three frequencies -- high, very high and ultra high -- variously combined with amplitude modulation, frequency hopping spread spectrum, narrow-band frequency modulation, single-side-band or wide-band frequency modulation. Annotations on the clear source audio signal, e.g., time boundaries for the duration of speech activity, were projected onto the corresponding eight channels recorded from the radio receivers.

Data

The source audio consists of conversational telephone speech recordings collected by LDC: (1) data collected for the RATS program from Levantine Arabic, Farsi, Pashto and Urdu speakers; and (2) material from the Fisher English (LDC2004S13, LDC2005S13), and Fisher Levantine Arabic telephone studies (LDC2007S02), as well as from CALLFRIEND Farsi (LDC2014S01).

Annotation was performed in three steps. LDC's automatic speech activity detector was run against the audio data to produce a speech segmentation for each file. Manual first pass annotation was then performed as a quick correction of the automatic speech activity detection output. Finally, in a manual second pass annotation step, annotators reviewed first pass output and made adjustments to segments as needed.

All audio files are presented as single-channel, 16-bit PCM, 16000 samples per second; lossless FLAC compression is used on all files; when uncompressed, the files have typical "MS-WAV" (RIFF) file headers.

Samples

Please view this audio sample and annotation sample.

Updates

None at this time.

Acknowledgment

This material is based upon work supported by the Defense Advanced Research Projects Agency (DARPA) under Contract No. D10PC20016. The content does not necessarily reflect the position or the policy of the Government, and no official endorsement should be inferred.

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