Datasets:
audio_id
stringlengths 14
14
| speaker_id
int64 6.51k
19.2k
| gender
stringclasses 4
values | age
stringclasses 15
values | duration
float64 0
20.1
| normalized_text
stringlengths 2
109
|
---|---|---|---|---|---|
006512-0054527 | 6,512 | male | 13-17 | 5.64 | núna ætlar karl að hugsa um mig svaraði bella fyrir hönd þeirra beggja |
006512-0054528 | 6,512 | male | 13-17 | 3.54 | liti ekki á hann tímunum saman |
006512-0054529 | 6,512 | male | 13-17 | 3.36 | sýndi ekki mikinn áhuga |
006512-0054530 | 6,512 | male | 13-17 | 5.46 | lagði svo af með láði list sem var góð og traust |
006512-0054531 | 6,512 | male | 13-17 | 6.18 | kristín var farin að hitta elísabetu halldórsdóttur og kanna líðan hennar |
006514-0054542 | 6,514 | male | 13-17 | 5.06 | hektor starði forviða á hana |
006514-0054543 | 6,514 | male | 13-17 | 5.94 | markmiðið er að komast beint austur er það ekki |
006514-0054544 | 6,514 | male | 13-17 | 8.68 | fyrr eða síðar hverfa ónauðsynlegu hjónabandshömlurnar ein af annarri |
006514-0054545 | 6,514 | male | 13-17 | 5.11 | systir þín kallaði hana ljónatemjara |
006514-0054546 | 6,514 | male | 13-17 | 7.2 | þeir segjast báðir óviljugir að taka að sér starf ráðherrans |
006517-0054582 | 6,517 | female | 13-17 | 7.08 | á stéttinni fyrir framan hótelið fræga standa tveir menn með hatta |
006517-0054583 | 6,517 | female | 13-17 | 2.99 | fylgdu þeim fram og til baka |
006517-0054584 | 6,517 | female | 13-17 | 4.31 | það hafði ótal sinnum verið tekið upp á hana |
006517-0054585 | 6,517 | female | 13-17 | 5.97 | hann er ekki sami hrokagikkurinn og sum börn sem maður rekst á |
006517-0054586 | 6,517 | female | 13-17 | 5.12 | hann virtist allsendis óhræddur við draugana í dalnum |
006518-0054638 | 6,518 | male | 13-17 | 4.14 | þakka yður ósköp vel fyrir segir stúlkan og hneigir sig |
006518-0054639 | 6,518 | male | 13-17 | 2.94 | en á honum var ekkert að finna |
006518-0054640 | 6,518 | male | 13-17 | 7.08 | hins vegar átti ísraelsher hugsanlega harma að hefna gagnvart heyrnardaufri stjúpmóður hans |
006518-0054641 | 6,518 | male | 13-17 | 2.88 | nema að hún keypti það ekki |
006519-0054642 | 6,519 | male | 13-17 | 4.13 | þá var röð myndanna breytt á milli umferða |
006519-0054643 | 6,519 | male | 13-17 | 3.53 | ég get bara ekki munað hvað það var |
006519-0054644 | 6,519 | male | 13-17 | 4.09 | hannes er eldrauður í framan |
006519-0054645 | 6,519 | male | 13-17 | 4.5 | hvur andskotinn brotið af brísingameninu |
006519-0054646 | 6,519 | male | 13-17 | 4.41 | en ég veit hvar þeir eru sagði edda |
006521-0054652 | 6,521 | female | 13-17 | 6.83 | afsakið herra segir afgreiðslumaðurinn og tekur húfuna sína varlega ofan |
006521-0054653 | 6,521 | female | 13-17 | 5.29 | hafði javert orðið vör við þennan örlitla skjálfta |
006521-0054654 | 6,521 | female | 13-17 | 3.39 | kemur hitinn virkilega úr þessu |
006521-0054655 | 6,521 | female | 13-17 | 7.85 | rafmagnsleysið á dögunum er rökrétt afleiðing pólitískra ákvarðana undanfarinna missera |
006523-0054662 | 6,523 | male | 13-17 | 5.25 | móðir mín var þá gömluð og gleymin og líklega saknaði ég hennar |
006523-0054663 | 6,523 | male | 13-17 | 2.83 | hann er enn ólofaður |
006523-0054664 | 6,523 | male | 13-17 | 4.32 | hvert og eitt dna próf er tímafrekt |
006523-0054665 | 6,523 | male | 13-17 | 4.55 | sést nokkuð í gegnum svona glerauga er það ekki bara upp á punt |
006523-0054666 | 6,523 | male | 13-17 | 3.62 | varst þú þar stödd við aftökuna |
006524-0054668 | 6,524 | female | 13-17 | 3.76 | sævar lofaði að hringja í hann daginn eftir |
006524-0054669 | 6,524 | female | 13-17 | 3.62 | þess gerist ekki þörf sagði hún |
006524-0054671 | 6,524 | female | 13-17 | 4.27 | fyrri og seinni kona og alls fjögur börn |
006520-0054672 | 6,520 | female | 13-17 | 3.62 | þessi glæpur er tvíhöfða |
006520-0054674 | 6,520 | female | 13-17 | 4.41 | hún reyndi að bregða ekki svip |
006525-0054677 | 6,525 | female | 13-17 | 4.97 | hvert og eitt dna próf er tímafrekt |
006525-0054678 | 6,525 | female | 13-17 | 7.24 | þrátt fyrir glæsimennsku sína mistekst sigmundi ætlunarverk sitt og þrándur hefur betur |
006525-0054679 | 6,525 | female | 13-17 | 4.55 | hugsa sér allt sem úrskeiðis getur farið |
006525-0054680 | 6,525 | female | 13-17 | 4.41 | þórður er ekki að mínu skapi |
006525-0054681 | 6,525 | female | 13-17 | 3.81 | jæja við sjáumst þá sagði hún |
006525-0054687 | 6,525 | female | 13-17 | 5.48 | þá var fólk ekki heldur að springa úr offitu eins og núna |
006525-0054688 | 6,525 | female | 13-17 | 4.04 | þetta var nærmynd og þau skellihlæjandi |
006525-0054690 | 6,525 | female | 13-17 | 3.62 | auk þess sækir þú um brauð |
006525-0054691 | 6,525 | female | 13-17 | 5.06 | við verðum að stöðva loka áður en hann nær að eyðileggja göngin |
006514-0054692 | 6,514 | male | 13-17 | 6.59 | húsið hans kuba er í brekku og þar er stór kjallari |
006514-0054693 | 6,514 | male | 13-17 | 5.67 | öll pörin á gólfinu eru á leiðinni í sömu átt |
006514-0054694 | 6,514 | male | 13-17 | 4.46 | nú sting ég olnbogunum aftur í dýnuna |
006514-0054695 | 6,514 | male | 13-17 | 11.33 | vopnaeftirlitsmenn sameinuðu þjóðirnar hafi verið lítt dulbúnir njósnarar að gæta hagsmuna bandaríkjastjórnar |
006514-0054696 | 6,514 | male | 13-17 | 2.93 | nú er gaman að lifa |
006526-0054702 | 6,526 | female | 13-17 | 4.13 | best að flýta sér að setja glasið á borð |
006526-0054703 | 6,526 | female | 13-17 | 4.04 | orðið ástríðuglæpur er ekki lengur til hjá lögreglunni |
006526-0054705 | 6,526 | female | 13-17 | 3.58 | þó að ekkert bendi til þess |
006526-0054706 | 6,526 | female | 13-17 | 4.32 | þá gæti verið betra að hafa nýjan mann með honum |
006527-0054707 | 6,527 | male | 13-17 | 3.67 | ég skal laga te |
006527-0054708 | 6,527 | male | 13-17 | 3.62 | en hafðir viðkomu á salerninu |
006527-0054709 | 6,527 | male | 13-17 | 4.46 | best er að sorgin sé ósýnileg |
006527-0054710 | 6,527 | male | 13-17 | 4.6 | hún er öll varðveitt í flateyjarbók |
006528-0054712 | 6,528 | male | 13-17 | 3.76 | það væri ekki rökrétt |
006528-0054713 | 6,528 | male | 13-17 | 3.53 | bjarni starði á hana |
006528-0054714 | 6,528 | male | 13-17 | 3.48 | þeir eru áfengir og ávanabindandi |
006528-0054715 | 6,528 | male | 13-17 | 2.97 | hans dauði er ekki sorglegur |
006528-0054716 | 6,528 | male | 13-17 | 5.48 | god dag sagði hann kumpánalega þegar ég gekk hjá |
006529-0054717 | 6,529 | female | 13-17 | 3.11 | sama hvað við reynum |
006529-0054719 | 6,529 | female | 13-17 | 4.09 | þetta eru ekki bestu skilyrðin til að kynnast honum |
006529-0054720 | 6,529 | female | 13-17 | 3.95 | jafnvel mýksta veðurfar virtist gera hann veikan |
006529-0054721 | 6,529 | female | 13-17 | 4.32 | þetta voru leiðindaspurningar en það yrði ekki við öllu séð |
006530-0054727 | 6,530 | female | 13-17 | 2.74 | hver er sá maður |
006530-0054728 | 6,530 | female | 13-17 | 3.16 | brjálæði sagði stenko |
006530-0054729 | 6,530 | female | 13-17 | 4.55 | það er engin tilviljun að farsíminn minn er enn á gistiheimilinu |
006530-0054730 | 6,530 | female | 13-17 | 3.3 | hvur djöfullinn sagði guttormur |
006530-0054731 | 6,530 | female | 13-17 | 4.6 | á hinn bóginn get ég ekki verið þekkt fyrir að hafna þessu boði |
006531-0054734 | 6,531 | male | 13-17 | 2.93 | hafði fólk grátið í jarðarför herdísar |
006532-0054737 | 6,532 | female | 13-17 | 3.63 | með og á móti |
006532-0054738 | 6,532 | female | 13-17 | 4.91 | hann byrjaði að ýlfra og svo heyrðist vængjasláttur |
006532-0054739 | 6,532 | female | 13-17 | 7.72 | engin húðflúr hugsaði hún eins og fangavörður að taka á móti nýjum fanga |
006532-0054740 | 6,532 | female | 13-17 | 4.78 | klukkan var hálftíu að morgni sunnudags |
006532-0054741 | 6,532 | female | 13-17 | 3.41 | það borgaði sig varla |
006533-0054744 | 6,533 | male | 13-17 | 4.6 | það var eitthvað svo ófullkomið við að vita ekki meira um hann |
006533-0054745 | 6,533 | male | 13-17 | 4.04 | hún nefndist nasser og réð ríkjum í egyptalandi |
006533-0054746 | 6,533 | male | 13-17 | 2.41 | bjarni sagði ekki orð |
006534-0054753 | 6,534 | male | 13-17 | 2.6 | þú rannsakar óvætti |
006534-0054754 | 6,534 | male | 13-17 | 3.95 | kannt þú að garga eins og krían |
006534-0054755 | 6,534 | male | 13-17 | 4.37 | það er tekið við patrik þegar hann er fjórtán ára |
006535-0054757 | 6,535 | female | 13-17 | 3.95 | ekki mér veðja ég |
006535-0054758 | 6,535 | female | 13-17 | 6.08 | átta mig svo á því að hver verður að hafa sinn smekk |
006535-0054759 | 6,535 | female | 13-17 | 5.53 | hvar skyldi hún hafa verið fyrstu jólin eftir skilnaðinn |
006535-0054760 | 6,535 | female | 13-17 | 4.92 | ég skal fara með honum sagði guttormur |
006535-0054761 | 6,535 | female | 13-17 | 4.41 | þau ganga hreint til verks hugsar hún |
006537-0054768 | 6,537 | female | 13-17 | 2.79 | ein í heiminum |
006537-0054769 | 6,537 | female | 13-17 | 3.72 | en ég verð að finna sólina sagði sóla |
006537-0054770 | 6,537 | female | 13-17 | 3.39 | hann hefur aldrei fyrirgefið okkur |
006538-0054772 | 6,538 | male | 13-17 | 6.36 | ronnie og florian höfðu verið með honum allan tímann |
006538-0054773 | 6,538 | male | 13-17 | 7.43 | en fólkið sem þeir eiga að starfa fyrir verðskuldar aðra og betri foringja |
006538-0054774 | 6,538 | male | 13-17 | 5.62 | eigandinn gerði sem betur fer ekki vart við sig á meðan |
006538-0054775 | 6,538 | male | 13-17 | 2.69 | þeir eru keppinautar |
006538-0054776 | 6,538 | male | 13-17 | 3.39 | ég skal vaka og passa þig |
006539-0054777 | 6,539 | male | 13-17 | 3.58 | ég ræði betur við þig seinna sagði hún |
Dataset Card for samromur_children
Dataset Summary
The Samrómur Children Corpus consists of audio recordings and metadata files containing prompts read by the participants. It contains more than 137000 validated speech-recordings uttered by Icelandic children.
The corpus is a result of the crowd-sourcing effort run by the Language and Voice Lab (LVL) at the Reykjavik University, in cooperation with Almannarómur, Center for Language Technology. The recording process has started in October 2019 and continues to this day (Spetember 2021).
Example Usage
The Samrómur Children Corpus is divided in 3 splits: train, validation and test. To load a specific split pass its name as a config name:
from datasets import load_dataset
samromur_children = load_dataset("language-and-voice-lab/samromur_children")
To load an specific split (for example, the validation split) do:
from datasets import load_dataset
samromur_children = load_dataset("language-and-voice-lab/samromur_children",split="validation")
Supported Tasks
automatic-speech-recognition: The dataset can be used to train a model for Automatic Speech Recognition (ASR). The model is presented with an audio file and asked to transcribe the audio file to written text. The most common evaluation metric is the word error rate (WER).
Languages
The audio is in Icelandic. The reading prompts were gathered from a variety of sources, mainly from the Icelandic Gigaword Corpus. The corpus includes text from novels, news, plays, and from a list of location names in Iceland. The prompts also came from the Icelandic Web of Science.
Dataset Structure
Data Instances
{
'audio_id': '015652-0717240',
'audio': {
'path': '/home/carlos/.cache/HuggingFace/datasets/downloads/extracted/2c6b0d82de2ef0dc0879732f726809cccbe6060664966099f43276e8c94b03f2/test/015652/015652-0717240.flac',
'array': array([ 0. , 0. , 0. , ..., -0.00311279,
-0.0007019 , 0.00128174], dtype=float32),
'sampling_rate': 16000
},
'speaker_id': '015652',
'gender': 'female',
'age': '11',
'duration': 4.179999828338623,
'normalized_text': 'eiginlega var hann hin unga rússneska bylting lifandi komin'
}
Data Fields
audio_id
(string) - id of audio segmentaudio
(datasets.Audio) - a dictionary containing the path to the audio, the decoded audio array, and the sampling rate. In non-streaming mode (default), the path points to the locally extracted audio. In streaming mode, the path is the relative path of an audio inside its archive (as files are not downloaded and extracted locally).speaker_id
(string) - id of speakergender
(string) - gender of speaker (male or female)age
(string) - range of age of the speaker: Younger (15-35), Middle-aged (36-60) or Elderly (61+).duration
(float32) - duration of the audio file in seconds.normalized_text
(string) - normalized audio segment transcription.
Data Splits
The corpus is split into train, dev, and test portions. Lenghts of every portion are: train = 127h25m, test = 1h50m, dev=1h50m.
To load an specific portion please see the above section "Example Usage".
Dataset Creation
Curation Rationale
In the field of Automatic Speech Recognition (ASR) is a known fact that the children's speech is particularly hard to recognise due to its high variability produced by developmental changes in children's anatomy and speech production skills.
For this reason, the criteria of selection for the train/dev/test portions have to take into account the children's age. Nevertheless, the Samrómur Children is an unbalanced corpus in terms of gender and age of the speakers. This means that the corpus has, for example, a total of 1667 female speakers (73h38m) versus 1412 of male speakers (52h26m).
These unbalances impose conditions in the type of the experiments than can be performed with the corpus. For example, a equal number of female and male speakers through certain ranges of age is impossible. So, if one can't have a perfectly balance corpus in the training set, at least one can have it in the test portion.
The test portion of the Samrómur Children was meticulously selected to cover ages between 6 to 16 years in both female and male speakers. Every of these range of age in both genders have a total duration of 5 minutes each.
The development portion of the corpus contains only speakers with an unknown gender information. Both test and dev sets have a total duration of 1h50m each.
In order to perform fairer experiments, speakers in the train and test sets are not shared. Nevertheless, there is only one speaker shared between the train and development set. It can be identified with the speaker ID=010363. However, no audio files are shared between these two sets.
Source Data
Initial Data Collection and Normalization
The data was collected using the website https://samromur.is, code of which is available at https://github.com/cadia-lvl/samromur. The age range selected for this corpus is between 4 and 17 years.
The original audio was collected at 44.1 kHz or 48 kHz sampling rate as *.wav files, which was down-sampled to 16 kHz and converted to *.flac. Each recording contains one read sentence from a script. The script contains 85.080 unique sentences and 90.838 unique tokens.
There was no identifier other than the session ID, which is used as the speaker ID. The corpus is distributed with a metadata file with a detailed information on each utterance and speaker. The madata file is encoded as UTF-8 Unicode.
The prompts were gathered from a variety of sources, mainly from The Icelandic Gigaword Corpus, which is available at http://clarin.is/en/resources/gigaword. The corpus includes text from novels, news, plays, and from a list of location names in Iceland. The prompts also came from the Icelandic Web of Science.
Annotations
Annotation process
Prompts were pulled from these corpora if they met the criteria of having only letters which are present in the Icelandic alphabet, and if they are listed in the DIM: Database Icelandic Morphology.
There are also synthesised prompts consisting of a name followed by a question or a demand, in order to simulate a dialogue with a smart-device.
Who are the annotators?
The audio files content was manually verified against the prompts by one or more listener (summer students mainly).
Personal and Sensitive Information
The dataset consists of people who have donated their voice. You agree to not attempt to determine the identity of speakers in this dataset.
Considerations for Using the Data
Social Impact of Dataset
This is the first ASR corpus of Icelandic children.
Discussion of Biases
The utterances were recorded by a smartphone or the web app.
Participants self-reported their age group, gender, and the native language.
Participants are aged between 4 to 17 years.
The corpus contains 137597 utterances from 3175 speakers, totalling 131 hours.
The amount of data due to female speakers is 73h38m, the amount of data due to male speakers is 52h26m and the amount of data due to speakers with an unknown gender information is 05h02m
The number of female speakers is 1667, the number of male speakers is 1412. The number of speakers with an unknown gender information is 96.
The audios due to female speakers are 78993, the audios due to male speakers are 53927 and the audios due to speakers with an unknown gender information are 4677.
Other Known Limitations
"Samrómur Children: Icelandic Speech 21.09" by the Language and Voice Laboratory (LVL) at the Reykjavik University is licensed under a Creative Commons Attribution 4.0 International (CC BY 4.0) License with the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.
Additional Information
Dataset Curators
The corpus is a result of the crowd-sourcing effort run by the Language and Voice Lab (LVL) at the Reykjavik University, in cooperation with Almannarómur, Center for Language Technology. The recording process has started in October 2019 and continues to this day (Spetember 2021). The corpus was curated by Carlos Daniel Hernández Mena in 2021.
Licensing Information
Citation Information
@misc{menasamromurchildren2021,
title={Samrómur Children Icelandic Speech 1.0},
ldc_catalog_no={LDC2022S11},
DOI={https://doi.org/10.35111/frrj-qd60},
author={Hernández Mena, Carlos Daniel and Borsky, Michal and Mollberg, David Erik and Guðmundsson, Smári Freyr and Hedström, Staffan and Pálsson, Ragnar and Jónsson, Ólafur Helgi and Þorsteinsdóttir, Sunneva and Guðmundsdóttir, Jóhanna Vigdís and Magnúsdóttir, Eydís Huld and Þórhallsdóttir, Ragnheiður and Guðnason, Jón},
publisher={Reykjavík University}
journal={Linguistic Data Consortium, Philadelphia},
year={2019},
url={https://catalog.ldc.upenn.edu/LDC2022S11},
}
Contributions
This project was funded by the Language Technology Programme for Icelandic 2019-2023. The programme, which is managed and coordinated by Almannarómur, is funded by the Icelandic Ministry of Education, Science and Culture.
The verification for the dataset was funded by the the Icelandic Directorate of Labour's Student Summer Job Program in 2020 and 2021.
Special thanks for the summer students for all the hard work.
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