Datasets:
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 interferersB_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/andASR_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).
- Downloads last month
- 101