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PersonaMix

Controlled bilingual (Kazakh–English) benchmark for target-speaker ASR and target-presence detection on overlapping speech, released with Persona-ASR.

Four speakers (two female, two male) each read 11 scripted sentences in both Kazakh and English. Mixtures span 1–3 interfering speakers and SNRs of −3, 0, +3, +6 dB, under same-language (A) and cross-language (B) enrollment; the cross-language condition enrolls a speaker in one language and transcribes them in the other.

Structure

  • mixtures/ — overlapping-speech mixtures by condition:
    • A_samelang_{1,2,3}int/ — same-language enrollment, 1–3 interferers
    • B_crosslang_{1,2,3}int/ — cross-language enrollment, 1–3 interferers
  • experiment_jsons/ — evaluation manifests per condition and SNR:
    • *_asr.json — target-speaker ASR (positive trials, with target transcript)
    • *_cls.json — target-presence detection (positive + negative trials)
    • all_snr{-3,0,3,6}dB.json — pooled manifests per SNR
  • experiments.zip — the whole benchmark as a single archive.
  • ASR_88/ and ASR_88 - {F1,F2,M1,M2}.csv — the 88 source recordings (4 speakers × 11 sentences × 2 languages) and per-speaker scripts.

Manifest fields (experiment_jsons/*.json)

Field Description
mixture_audio Overlapping mixture
enrollment_audio Target-speaker enrollment utterance
transcript Target reference transcript
sample_type positive / negative (target present / absent)
target_speaker Target speaker id (F1, F2, M1, M2)
enrollment_lang, mixture_lang Enrollment vs. mixture language (equal = same-lang, differ = cross-lang)
snr_db Target-to-interferer SNR
enrollment_sentence, target_sentence, interferers Content and interference metadata

Speakers

Four speakers, anonymized as F1 and F2 (female) and M1 and M2 (male).

Generation

data_generation/personamix/generate_personamix.py in the Persona-ASR repository regenerates the manifests and mixtures from ASR_88/. The manifests it writes are identical to the released ones, and in our checks the mixtures match the released audio to within one 16-bit sample value. The script's docstring describes the mixing recipe.

License and citation

Released under CC BY 4.0. Please cite Persona-ASR.

@article{meiramov2026personaasr,
  author  = {Meiramov, Rakhat and Rakhimzhanova, Tomiris and Taibassarov, Adil and Makhataeva, Zhanat and Varol, Huseyin Atakan},
  title   = {Persona-ASR: Bilingual Target-Speaker Speech Recognition for Kazakh--English Overlapping Speech},
  journal = {Machine Learning and Knowledge Extraction},
  year    = {2026},
  volume  = {8},
  number  = {8},
  pages   = {246},
  doi     = {10.3390/make8080246}
}

Funding

This research is funded by the Committee of Science of the Ministry of Science and Higher Education of the Republic of Kazakhstan (Grant No. BR24993001).

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