Datasets:

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Datasets
WebDataset
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ISSAI_CV_330/test_sf/31_2_2_1_178_1
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ISSAI_CV_330/test_sf/45_1_2_8_613_1
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ISSAI_CV_330/test_sf/59_2_2_5_519_1
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ISSAI_CV_330/test_sf/6_1_2_3_1248_1
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ISSAI_CV_330/test_sf/35_1_2_5_448_1
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ISSAI_CV_330/test_sf/38_2_2_5_1121_1
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ISSAI_CV_330/test_sf/124_2_2_2_179_1
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ISSAI_CV_330/test_sf/79_2_2_4_901_1
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ISSAI_CV_330/test_sf/8_2_2_1_370_1
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ISSAI_CV_330/test_sf/1_2_2_2_951_1
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ISSAI_CV_330/test_sf/14_2_2_5_565_1
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ISSAI_CV_330/test_sf/35_1_2_8_68_1
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ISSAI_CV_330/test_sf/8_2_2_4_957_1
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ISSAI_CV_330/test_sf/64_2_2_5_866_1
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ISSAI_CV_330/test_sf/78_1_2_2_323_1
hf://datasets/issai/Multilingual_Speech_Commands_Dataset@6bd12fba6976f072f2cc15eff058b9dd24a218ee/ISSAI_CV_330.tar.gz
ISSAI_CV_330/test_sf/52_2_2_3_419_1
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ISSAI_CV_330/test_sf/135_1_2_5_136_1
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ISSAI_CV_330/test_sf/121_1_2_4_76_1
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ISSAI_CV_330/test_sf/141_1_2_1_59_1
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ISSAI_CV_330/test_sf/104_2_2_7_55_1
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ISSAI_CV_330/test_sf/135_1_2_5_138_1
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ISSAI_CV_330/test_sf/107_2_2_3_18_1
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ISSAI_CV_330/test_sf/35_2_2_1_861_1
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ISSAI_CV_330/test_sf/37_2_2_1_762_1
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ISSAI_CV_330/test_sf/136_2_2_8_54_1
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ISSAI_CV_330/test_sf/52_2_2_6_1248_1
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ISSAI_CV_330/test_sf/56_2_2_1_1114_1
hf://datasets/issai/Multilingual_Speech_Commands_Dataset@6bd12fba6976f072f2cc15eff058b9dd24a218ee/ISSAI_CV_330.tar.gz
ISSAI_CV_330/test_sf/14_1_2_6_1163_1
hf://datasets/issai/Multilingual_Speech_Commands_Dataset@6bd12fba6976f072f2cc15eff058b9dd24a218ee/ISSAI_CV_330.tar.gz
ISSAI_CV_330/test_sf/9_1_2_5_80_1
hf://datasets/issai/Multilingual_Speech_Commands_Dataset@6bd12fba6976f072f2cc15eff058b9dd24a218ee/ISSAI_CV_330.tar.gz
ISSAI_CV_330/test_sf/18_1_2_9_30_1
hf://datasets/issai/Multilingual_Speech_Commands_Dataset@6bd12fba6976f072f2cc15eff058b9dd24a218ee/ISSAI_CV_330.tar.gz
ISSAI_CV_330/test_sf/9_2_2_6_602_1
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ISSAI_CV_330/test_sf/93_2_2_9_1153_1
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ISSAI_CV_330/test_sf/86_1_2_5_659_1
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ISSAI_CV_330/test_sf/57_1_2_8_230_1
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ISSAI_CV_330/test_sf/57_1_2_4_104_1
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ISSAI_CV_330/test_sf/58_1_2_6_293_1
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ISSAI_CV_330/test_sf/102_2_2_8_1_1
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ISSAI_CV_330/test_sf/25_1_2_7_1181_1
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ISSAI_CV_330/test_sf/57_2_2_1_190_1
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ISSAI_CV_330/test_sf/10_1_2_9_526_1
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ISSAI_CV_330/test_sf/37_1_2_6_816_1
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ISSAI_CV_330/test_sf/3_2_2_8_693_1
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ISSAI_CV_330/test_sf/86_1_2_8_127_1
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ISSAI_CV_330/test_sf/125_2_2_1_159_1
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ISSAI_CV_330/test_sf/136_1_2_4_36_1
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ISSAI_CV_330/test_sf/27_1_2_6_149_1
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ISSAI_CV_330/test_sf/38_1_2_9_392_1
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ISSAI_CV_330/test_sf/8_2_2_9_749_1
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ISSAI_CV_330/test_sf/38_2_2_2_36_1
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ISSAI_CV_330/test_sf/36_1_2_7_865_1
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ISSAI_CV_330/test_sf/3_1_2_5_810_1
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ISSAI_CV_330/test_sf/9_2_2_6_326_1
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ISSAI_CV_330/test_sf/81_2_2_7_1173_1
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ISSAI_CV_330/test_sf/101_2_2_7_178_1
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ISSAI_CV_330/test_sf/29_1_2_7_225_1
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Hugging Face Dataset Card

Dataset Name: Multilingual End-to-End Speech Recognition for Kazakh, Russian, and English

Repository: https://github.com/IS2AI/MultilingualASR

Summary: This repository contains the recipe for reproducing the experiments detailed in the paper "A Study of Multilingual End-to-End Speech Recognition for Kazakh, Russian, and English" (https://arxiv.org/abs/2108.01280). The work focuses on training a single end-to-end (E2E) automatic speech recognition (ASR) model for Kazakh, Russian, and English. The research compares monolingual and multilingual models (with combined and independent output grapheme sets), investigates the impact of language models (LMs) and data augmentation techniques, and achieves comparable performance to monolingual baselines (20.9% and 20.5% average word error rates for the best monolingual and multilingual models respectively on the combined test set). Pre-trained models are provided.

Citation:

Please cite the original paper: https://arxiv.org/pdf/2108.01280

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