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Balalaika pipeline enhances Russian speech data with prosody-aware annotations

Researchers have developed Balalaika, an open-source pipeline designed for annotating Russian speech data with a focus on prosody. This system integrates semantic voice activity detection, multi-ASR ensembling, and automatic quality filtering to create a 5.1k-hour corpus. The pipeline also enriches the text with punctuation, lexical stress, and phoneme normalization, demonstrating consistent improvements in speech denoising and text-to-speech synthesis. AI

Summary written by gemini-2.5-flash-lite from 1 source. How we write summaries →

IMPACT Introduces a new pipeline for processing and annotating Russian speech data, potentially improving downstream speech synthesis and denoising models.

RANK_REASON This is a research paper describing a new data annotation pipeline for speech. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.CL →

COVERAGE [1]

  1. arXiv cs.CL TIER_1 · Kirill Borodin, Nikita Vasiliev, Vasiliy Kudryavtsev, Maxim Maslov, Mikhail Gorodnichev, Grach Mkrtchian ·

    Balalaika: Data-Centric, Prosody-Aware Annotation Pipeline for Russian Speech

    arXiv:2507.13563v2 Announce Type: replace Abstract: We introduce Balalaika, an open-source, data-centric pipeline for processing audio and producing prosody-aware annotations. It combines semantic VAD for context-preserving segmentation, multi-ASR ensembling with ROVER consensus …