Samrómur Children Icelandic Speech 1.0

Item Name: Samrómur Children Icelandic Speech 1.0
Author(s): Carlos Daniel Hernández Mena, Michal Borsky, David Mollberg, Smári Freyr Guðmundsson, Staffan Hedström, Ragnar Pálsson, Ólafur Helgi Jónsson, Sunneva Þorsteinsdóttir, Jóhanna Vigdís Guðmundsdóttir, Eydis Huld Magnusdottir, Ragnheiður Þórhallsdóttir, Jon Gudnason
LDC Catalog No.: LDC2022S11
ISLRN: 228-981-226-601-4
Release Date: November 15, 2022
Member Year(s): 2022
DCMI Type(s): Sound, Text
Sample Type: flac
Sample Rate: 16000
Data Source(s): web collection
Application(s): speaker identification, speaker verification, speech recognition
Language(s): Icelandic
Language ID(s): isl
License(s): Samrómur Children Icelandic Speech 1.0 Agreement (For-Profit)
Samrómur Children Icelandic Speech 1.0 Agreement (Non-Member)
Samrómur Children Icelandic Speech 1.0 Agreement (Not-For-Profit)
Online Documentation: LDC2022S11 Documents
Licensing Instructions: Subscription & Standard Members, and Non-Members
Citation: Hernández Mena, Carlos Daniel, et al. Samrómur Children Icelandic Speech 1.0 LDC2022S11. Web Download. Philadelphia: Linguistic Data Consortium, 2022.
Related Works: View


Samrómur Children Icelandic Speech 1.0 was developed by the Language and Voice Lab, Reykjavik University in cooperation with Almannarómur, Center for Language Technology. The corpus contains 131 hours of Icelandic prompted speech from 3,175 speakers (children, aged 4-17 years) representing 137,597 utterances.

This version 1.0 is equivalent to "Samrómur Children Icelandic Speech 21.09" as used by the Language Technology Programme for Icelandic 2019-2023.


Speech data was collected between October 2019 and September 2021 using the Samrómur website which displayed prompts to participants. The prompts were mainly from The Icelandic Gigaword Corpus, which includes text from novels, news, plays, and from a list of location names in Iceland. Additional prompts were taken from the Icelandic Web of Science and others were created by combining a name followed by a question or a demand. Prompts and speaker metadata are included in the corpus.

The audio data is divided into train, dev, and test sets and is presented as flac compressed, single channel, 16 kHz, 16-bit linear PCM.


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