datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
open-ko-s2s-eval-artifacts
Open Ko-S2S 평가 산출물 (감사용)
⚠️ KsponSpeech 참조 전사는 해시로 대체돼 있습니다
KsponSpeech 는 AI Hub 배포 데이터로 재배포 제한이 있을 수 있어, kspon 런의
ref 컬럼을 ref_sha256 으로 대체했습니다(전사 원문 미포함). 모델 출력(hyp)과
채점 결과(cer_err/cer_len/cer)는 우리 산출물이라 그대로 공개합니다.
Zeroth 런은 원본이 CC BY 4.0(OpenSLR #40)이라
ref 원문을 그대로 담고 있습니다.
라이선스 보유자의 검증 절차
AI Hub 에서 KsponSpeech 를 정당하게 받은 분은 다음으로 우리 수치를 검증할 수 있습니다.
리더보드 저장소의 eval/datasets_ko.py 에서 clean_kspon() 을 가져옵니다.
자기 사본의 원 전사에 clean_kspon() 을 적용합니다. 결과가 목록이면… See the full description on the dataset page: https://huggingface.co/datasets/baryonlabs/open-ko-s2s-eval-artifacts.polish-tedx-asr-eval
Polish-TEDx-ASR-Eval
A dataset for evaluating automatic speech recognition (ASR) systems for Polish in the domain of TEDx public talks.
Contains audio segments from Polish TEDx talks available on YouTube (CC BY-NC-ND 4.0) and synthetic speech generated with KugelAudio (MIT), with manually created and cross-verified transcriptions. Created as part of the course "Workshops on Evaluation of Speech Recognition Systems" (ZWESUI, AMU 2026) by Group 1.
Statistics… See the full description on the dataset page: https://huggingface.co/datasets/s512757/polish-tedx-asr-eval.YouTube-Evaluation-Set
Awaaz se Alfaaz — YouTube Evaluation Set
This dataset is the realistic multi-speaker evaluation set used in Awaaz se Alfaaz, accepted at LaTeLL 2026 — "Enhancing Urdu ASR with Whisper v3: Fine-Tuning on Latest Datasets and Realistic Multi-Speaker Evaluation with SLM Post-Processing." It contains 30 short-form Urdu YouTube videos (YouTube Shorts) covering a mix of news, sports, and current affairs content, along with human annotated gold transcripts and transcripts produced by… See the full description on the dataset page: https://huggingface.co/datasets/awaaz-se-alfaaz/YouTube-Evaluation-Set.2026-dwesui-g02-kulinarna
DWESUI 2026 - Grupa 2 - kulinarna (PIEROGA)
Robocza/archiwalna kopia zbioru ewaluacyjnego ASR zbudowanego przez studentow kursu
Warsztaty z ewaluacji systemow rozpoznawania mowy (UAM WMI), edycja 2026, tryb dzienny.
Zespol (atrybucja): Grupa 2 (DWESUI 2026)
Zrodlo oryginalne: https://huggingface.co/datasets/s479246/dwesui-grupa-2-kulinarna
Domena: kulinarna
Licencja zrodla: nagrania YouTube CC-BY/CC-BY-SA + TTS
Status: kopia publiczna w organizacji kursowej (zespół opublikował… See the full description on the dataset page: https://huggingface.co/datasets/uam-wmi-asr-eval-labs/2026-dwesui-g02-kulinarna.gemma-4-public-bench-eval
Gemma 4 (e4b & 12b) — Public ASR Benchmark (Decoded Hypotheses + WER)
Decoded transcripts and word-level error metrics from Gemma 4 Unified
(the encoder-free, natively audio-capable models) run as automatic speech
recognition (ASR) systems on three standard English test sets. Two models are
evaluated — gemma4:e4b (8B params) and gemma4:12b. Everything was
produced locally with ollama; the evaluation tool
(eval_asr.py) is included so the numbers are fully reproducible.
Gemma 4… See the full description on the dataset page: https://huggingface.co/datasets/huckiyang/gemma-4-public-bench-eval.