CALLFRIEND Russian Speech

Item Name: CALLFRIEND Russian Speech
Author(s): David Miller, Kevin Walker, David Graff, Alexandra Canavan
LDC Catalog No.: LDC2023S08
ISLRN: 607-488-391-299-4
Release Date: September 15, 2023
Member Year(s): 2023
DCMI Type(s): Sound
Sample Type: pcm
Sample Rate: 8000
Data Source(s): telephone conversations
Project(s): LID
Application(s): language identification
Language(s): Russian
Language ID(s): rus
License(s): LDC User Agreement for Non-Members
Online Documentation: LDC2023S08 Documents
Licensing Instructions: Subscription & Standard Members, and Non-Members
Citation: Miller, David, et al. CALLFRIEND Russian Speech LDC2023S08. Web Download. Philadelphia: Linguistic Data Consortium, 2023.
Related Works: View


CALLFRIEND Russian Speech (LDC2023S08) was developed by the Linguistic Data Consortium (LDC) and consists of approximately 48 hours of telephone conversations (100 recordings) between native speakers of Russian. The calls were recorded in 1999 as part of the CALLFRIEND collection. One hundred native Russian speakers living in the continental United States each made a single phone call, lasting up to 30 minutes, to a family member or friend living in the United States.

Corresponding transcripts and a lexicon are available in CALLFRIEND Russian Text (LDC2023T09).

The CALLFRIEND series is a collection of telephone conversations in several languages conducted by LDC in support of language identification technology development. Languages covered in the collection include American English, Canadian French, Egyptian Arabic, Farsi, German, Hindi, Japanese, Korean, Mandarin Chinese, Russian, Spanish, Tamil and Vietnamese.


All recordings involved domestic calls routed through the automated telephone collection platform at LDC and were stored as 2-channel (4-wire) 8-KHz mu-law samples taken directly from a public telephone network via a T-1 circuit. Each audio file is a FLAC-compressed MS-WAV (RIFF) format audio file containing 2-channel, 8-KHz, 16-bit PCM sample data.

This release includes call metadata, including speaker gender, the number of speakers on each channel and call duration.


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