Russian through Switched Telephone Network (RuSTeN)

registration: 2007/06/20 08:35:52, last modified: 2016/08/17 13:26:27
title
  • Russian through Switched Telephone Network (RuSTeN)
title.abbreviation
  • RuSTeN
title.alternative
creator
  • researcher Anrey Raev
  • researcher Serguei Koval
  • researcher Natalia Smirnova
  • researcher Daria Khitrova
  • researcher Vitaly Stepanov
subject
  • speech corpus
subject.linguisticField
  • phonetics
  • phonology
subject.monoMultilingual
  • monolingual
subject.resourceSubject
  • corpus
description
  • *Introduction*

    This file contains documentation on the Russian through Switched Telephone Network (RuSTeN), Linguistic Data Consortium (LDC) catalog number LDC2006S34 and ISBN 1-58563-388-7.

    This corpus was developed as part of ?Trawl? (Automatic Voice Identification System in Telephone Channel). The purpose of the project was to develop software for automatic identification of speakers based on voice samples acquired through telephone channels. The training of the system was performed with the telephone speech corpus RuSTeN.

    *Data*

    The RuSTeN (Russian through Switched Telephone Network) database was recorded between March 2001 and February 2003 by Speech Technology Center using the "forget-me-not" professional telephone recording and archiving software package developed by STC. The files were recorded with sample frequency 11025 Hz, one-channel, 16-bit linear.

    Each of the speakers made at least five calls from different locations and/or telephone sets. Most of the calls were made from home or an office environment with uncontrolled noise level. Additionally, one call per speaker was made from a public telephone (with either street or metro station noise in the background). The recordings are spontaneous (sometimes guided by the near-end speaker) conversations between the caller and the speech database collector on various subjects (the weather, the caller's biography, hobbies, etc.) and include approximately 150 seconds of the far-end and at least five seconds of the near-end speaker. Besides, each time the caller was asked to utter the usual digits set (0-9) and the words "yes" and "no."

    The time interval between two successive sessions is at least two days. The database contains 125 speakers (far-end), 58 male and 67 female. Each far-end speaker is represented by at least five speech files. The sound files are in the wav-format. The speech filenames contain the following information: FFF (far-end speaker number) and SS (session number).

    *Samples*

    For an example of the data in this corpus, please review this audio sample.
description.price *This metadata is only as a guide
description.language
  • English
description.inputDevice
  • fixed_line_telephone
description.inputEnvironment
  • office_room home or office environment with uncontrolled noise level
  • noisy_condition public telephone with either street or metro station noise in the background
description.speakingStyle
  • spontaneous_speech
description.speechMode
  • dialogue
description.samplingRate
  • 11.025 kHz
description.additionalData
  • analysis_parameter speaker information (gender, age, education, city (region) born and raised, current residence)
publisher
contributor
contributor.attribute.author.motherTongue
contributor.attribute.author.dialect
contributor.attribute.author.level
contributor.attribute.author.age
contributor.attribute.author.gender
contributor.attribute.speaker.motherTongue
  • native
contributor.attribute.speaker.dialect
  • standard_dialect
contributor.attribute.speaker.level
  • amateur
contributor.attribute.speaker.age
  • adult
contributor.attribute.speaker.gender
  • male
  • female
contributor.attribute.speaker.number
  • number_of_male_speakers 58
  • number_of_female_speakers 67
  • number_of_total_speakers 125
date.created
  • 2001-00-00 2003-00-00
date.issued
  • 2006-07-21
date.modified
type
  • Sound
type.discourseType
type.linguisticType
  • primary_text
type.purpose
  • developing_technologies speaker identification
  • developing_technologies speaker verification
  • developing_technologies speech recognition
  • developing_technologies to develop software for automatic identification of speakers based on voice samples acquired through telephone channels
type.style
  • speech dialogue
type.form
  • unfixed
type.sentence
  • short
  • long
type.annotation
type.annotationSample
type.sample
format.extent
  • 11025 Hz
  • 16 bit linear pcm 1 channeldatabase contains 125 speakers (far-end)
  • Each far-end speaker is represented by at least five speech files
  • Corpus size: 4404019 KB
format.medium
  • DVD
format.encoding
format.markup
format.functionality
identifier
identifier.doi
identifier.islrn
  • 301-264-944-856-8
source
  • telephone conversations
language
  • Russian
language.area
  • Europe
relation
  • isReferencedBy Switched Telephone Network (RuSTeN)catalog number LDC2006S34 and ISBN 1-58563-388-7.
relation.utilization *This metadata is automatically extracted
coverage.temporal
coverage.spacial
rights