datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
apptek_callcenter_dialogues
AppTek Call-Center Dialogues: A Multi-Accent Long-Form Benchmark for English ASR
AppTek Call-Center Dialogues is a long-form conversational speech dataset for automatic speech recognition (ASR), featuring diverse English accents
across multiple service-oriented domains and designed to evaluate models on realistic call-center interactions.
128.6 hours of speech
14 English accent groups
16 service domains
5–15 minute conversations (long-form)
Split-channel audio (one… See the full description on the dataset page: https://huggingface.co/datasets/apptek-com/apptek_callcenter_dialogues.EchoX-Dialogues-Plus
EchoX-Dialogues-Plus: Training Data Plus for EchoX: Towards Mitigating Acoustic-Semantic Gap via Echo Training for Speech-to-Speech LLMs
🐈⬛ Github ｜ 📃 Paper ｜ 🚀 Space
🧠 EchoX-8B ｜ 🧠 EchoX-3B ｜ 📦 EchoX-Dialogues (base)
EchoX-Dialogues-Plus
EchoX-Dialogues-Plus extends KurtDu/EchoX-Dialogues with large-scale Speech-to-Speech (S2S) and Speech-to-Text (S2T) dialogues.
All assistant/output speech is synthetic (single, consistent timbre for S2S). Texts are from… See the full description on the dataset page: https://huggingface.co/datasets/KurtDu/EchoX-Dialogues-Plus.apptek_callcenter_dialogues
AppTek Call-Center Dialogues: A Multi-Accent Long-Form Benchmark for English ASR
AppTek Call-Center Dialogues is a long-form conversational speech dataset for automatic speech recognition (ASR), featuring diverse English accents
across multiple service-oriented domains and designed to evaluate models on realistic call-center interactions.
128.6 hours of speech
14 English accent groups
16 service domains
5–15 minute conversations (long-form)
Split-channel audio (one speaker… See the full description on the dataset page: https://huggingface.co/datasets/hussxamg04/apptek_callcenter_dialogues.AtlasSpeech-Dialogues
AtlasSpeech Dialogues
AtlasSpeech Dialogues contains consented conversational audio segments and aligned transcripts for robustness research.
Data fields
Each record contains an audio reference, transcript, speaker split, and recording environment tag.
Access notes
Users should retain the supplied split identifiers when reporting benchmark results.
Documentation stewardship
Dataset: toolathlonEval/AtlasSpeech-Dialogues
Standard: Open… See the full description on the dataset page: https://huggingface.co/datasets/toolathlonEval/AtlasSpeech-Dialogues.