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Golos: Russian Dataset for Speech Research

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arxiv 2106.10161 v1 pith:N5MTQJTJ submitted 2021-06-18 eess.AS

Nikolay Karpov , Alexander Denisenko , Fedor Minkin This is my paper · ORCID
classification eess.AS
keywords datasetcorpusmodelspeechacousticaudiogolosresearch
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This paper introduces a novel Russian speech dataset called Golos, a large corpus suitable for speech research. The dataset mainly consists of recorded audio files manually annotated on the crowd-sourcing platform. The total duration of the audio is about 1240 hours. We have made the corpus freely available to download, along with the acoustic model with CTC loss prepared on this corpus. Additionally, transfer learning was applied to improve the performance of the acoustic model. In order to evaluate the quality of the dataset with the beam-search algorithm, we have built a 3-gram language model on the open Common Crawl dataset. The total word error rate (WER) metrics turned out to be about 3.3% and 11.5%.

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Cited by 3 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. Dialogs: a studio-quality expressive conversational Russian speech corpus for dialog assistants

    eess.AS 2026-07 conditional novelty 6.0 of 10

    Dialogs is a new 20.6-hour studio-quality Russian conversational speech corpus with emotion labels and a VITS2 proof-of-concept.

  2. TEDI: Trustworthy and Ethical Dataset Indicators to Analyze and Compare Dataset Documentation

    cs.CY 2025-05 conditional novelty 6.0 of 10

    A new 143-indicator rubric applied to 114 human-voice datasets shows that documentation of consent, privacy, and harmful content is rare, and that scraping yields scale at the cost of documented ethical practices.

  3. The TEA-ASLP System for Multilingual Conversational Speech Recognition and Speech Diarization in MLC-SLM 2025 Challenge

    cs.SD 2025-07 conditional novelty 4.0 of 10

    Combining dual encoders, LID-routed MoE LoRA, and CTC prompts yields top challenge results for multilingual conversational ASR and speech diarization.

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