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.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.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.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.taiwan-conversation-context-100-domains
Taiwan Conversation Context 100 Domains
Dataset Description
Taiwan Conversation Context 100 Domains 是一套以台灣日常生活情境為核心設計的雙人對話文本資料集。
本資料集包含 100 個生活領域，每個領域各有 12,000 筆對話資料，總計約 1,200,000 筆對話樣本。每筆資料皆為雙人對話格式，包含 [A][B][A][B][A][B][A][B] 共 8 個發言，也就是 4 輪來回對話。
資料以繁體中文撰寫，並針對台灣在地語境設計，適合用於：
語音生成資料前處理
Text-to-Speech, TTS
Spoken Dialogue Generation
Conversational AI
Customer Service Dialogue Modeling
Role-play Dialogue Dataset
台灣繁體中文語音模型訓練
生活情境問答模型訓練
對話式 AI 助理訓練
RAG / Agent 測試資料… See the full description on the dataset page: https://huggingface.co/datasets/Ethan615/taiwan-conversation-context-100-domains.