datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
ContextASR-Bench
ContextASR-Bench: A Massive Contextual Speech Recognition Benchmark
Automatic Speech Recognition (ASR) has been extensively investigated, yet prior benchmarks have largely focused on assessing the acoustic robustness of ASR models, leaving evaluations of their linguistic capabilities relatively underexplored. This largely stems from the limited parameter sizes and training corpora of conventional ASR models, leaving them with insufficient world knowledge, which is crucial for… See the full description on the dataset page: https://huggingface.co/datasets/MrSupW/ContextASR-Bench.thai-contextasr-bench
Thai Contextual-Biasing ASR Benchmark
TL;DR
Does your Thai ASR system actually use the context you give it (e.g., a list of names, custom words from your own dictionary) — and does it hallucinate when the context is irrelevant?
Each utterance comes with a bias list: entity strings (brands, person names,
places) that may or may not be spoken in the audio, written the way a real Thai user
would write them — one list, mixed Thai and Latin script. A good system does… See the full description on the dataset page: https://huggingface.co/datasets/wayu-ai/thai-contextasr-bench.MM-ContextASR-Bench
MM-ContextASR Bench
Metadata and evaluation splits for Multimodal Conversational Context for
LLM-Based ASR: Data Construction, Training, and Benchmark.
Dataset summary
Config
Examples
Audio
Context
Primary metric
mm_contextasr
1,250 (250 current utterances × 5 histories)
1,439 WAV files included
Controlled user-assistant dialogue
entity Recall
kespeech
19,212
Source ID only
Same-speaker speech and transcript
CER, SER, entity Recall
cv_yue
3,525… See the full description on the dataset page: https://huggingface.co/datasets/lilonghao/MM-ContextASR-Bench.ePark_qing_jing_zu_yu_contextual_indigenous_language
FormosanBank publication status
This audio is associated with XML published in the public FormosanBank corpus and uses the same license recorded in that XML: CC BY-NC-SA 4.0. View the published XML. Publication approval is recorded on the corresponding FormosanBank Basecamp card.
FormosanBank/ePark_qing_jing_zu_yu_contextual_indigenous_language
Commercial AI Use is prohibited without prior written permission. See the FormosanBank Terms of Use and AI Use… See the full description on the dataset page: https://huggingface.co/datasets/FormosanBank/ePark_qing_jing_zu_yu_contextual_indigenous_language.asr-context-induced-leakage
When Helpful Context Leaks: Privacy Risks in Domain-Adapted ASR
Overview
SpeechLLMs are increasingly deployed in professional settings where domain customisation is standard practice: users supply context in prompts, fine-tune on proprietary recordings, or both. We identify and systematically investigate an overlooked privacy risk of such customisation: a model adapted to recognise domain-specific terminology can be nudged into transcribing a phonetically similar… See the full description on the dataset page: https://huggingface.co/datasets/maikezu/asr-context-induced-leakage.ContextASR-Bench
ContextASR-Bench: A Massive Contextual Speech Recognition Benchmark
Automatic Speech Recognition (ASR) has been extensively investigated, yet prior benchmarks have largely focused on assessing the acoustic robustness of ASR models, leaving evaluations of their linguistic capabilities relatively underexplored. This largely stems from the limited parameter sizes and training corpora of conventional ASR models, leaving them with insufficient world knowledge, which is crucial for… See the full description on the dataset page: https://huggingface.co/datasets/bsmu666/ContextASR-Bench.