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.apptek_callcenter_dialogues_travel_hospitality_no_transcripts
AppTek Call-Center Dialogues — Travel and Hospitality (No Transcripts)
This is a filtered derivative of AppTek Call-Center Dialogues, prepared for a specific use case.
Changes from the source dataset
Restricted the dataset to the travel and hospitality domains.
Removed the transcript field (text) entirely.
Kept the original audio and the domain, gender, and accent metadata.
Preserved the source dataset's test split.
This dataset has transcripts removed and is… See the full description on the dataset page: https://huggingface.co/datasets/josemancharo/apptek_callcenter_dialogues_travel_hospitality_no_transcripts.russian-call-center-speech-ru
📖 Описание на русском
ОписаниеКрупный датасет реальных записей колл-центров на русском языке.Телефонное качество, разговоры «клиент–оператор».Подходит для обучения систем ASR (распознавание речи), NLP, голосовых ассистентов и анализа диалогов.
Технические характеристики
Язык: русский
Общая продолжительность: ~832 часа
Формат: MP3
Каналы: моно (клиент и оператор в одном канале)
Частота дискретизации: 8000 Гц
Битрейт: 32 кбит/с
Метаданные: отсутствуют… See the full description on the dataset page: https://huggingface.co/datasets/MaratDV/russian-call-center-speech-ru.multilingual-call-center-speech-dataset
Multilingual Call Center Speech Recognition Dataset: 10,000 Hours
Dataset Summary
10,000 hours of real-world call center speech recordings in 7 languages with transcripts. Train speech recognition, sentiment analysis, and conversation AI models on authentic customer support audio. Covers support, sales, billing, finance, and pharma domains
Dataset Features
📊 Scale & Quality
10,000 hours of inbound & outbound calls
Real-world field… See the full description on the dataset page: https://huggingface.co/datasets/AxonData/multilingual-call-center-speech-dataset.Human-to-machine-Japanese-audio-call-center-conversations
Dataset Card for Japanese audio call center human to machine conversations
This dataset contains synthetic audio conversations in Japanese between human customers and machine agents, simulating real-world call center scenarios
Dataset Details
Dataset Description
Curated by: AIxBlock (aixblock.io)
Funded by [optional]: AIxBlock (aixblock.io)
Shared by [optional]: AIxBlock (aixblock.io)
Language(s) (NLP): Japanese
License: Creative Commons Attribution Non… See the full description on the dataset page: https://huggingface.co/datasets/AIxBlock/Human-to-machine-Japanese-audio-call-center-conversations.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.call-center-audio
Call Center Dataset - 13,000+ Hours
Dataset is a large audio dataset containing 13,000+ hours of real-world customer service calls from global call centers, featuring 90%+ unique speakers and time-stamped transcripts for accurate speech recognition, speaker diarization, and conversational AI model training. - Get the data
Dataset characteristics:
Characteristic
Data
Description
Audio of real customer service calls
Data types
Audio
Tasks
Speech… See the full description on the dataset page: https://huggingface.co/datasets/ud-nlp/call-center-audio.Eng-Filipino-Accented-audio-with-human-transcription-call-center-topicThis dataset contains 103+ hours of spontaneous English conversations spoken in a Filipino accent, recorded in a studio environment to ensure crystal-clear audio quality. The conversations are designed as role-play scenarios between agents and customers across a variety of call center domains.
🗣️ Speech Style: Natural, unscripted role-playing between native Filipino-accented English speakers, simulating real-world customer interactions.
🎧 Audio Format: High-quality stereo WAV files, recorded… See the full description on the dataset page: https://huggingface.co/datasets/AIxBlock/Eng-Filipino-Accented-audio-with-human-transcription-call-center-topic.french-call-center-speech-dataset
French Call Center Speech Dataset: 1,000+ Hours with Transcripts
1,000+ hours of real-world French call center audio with transcripts. Train speech recognition, sentiment analysis, and customer support AI models on authentic telephone conversations
Dataset Summary
Key Features
✅ 1,000+ hours of inbound & outbound calls✅ 100% French telephone conversations✅ Real-world audio - no synthetic data✅ Full transcripts in French and in English
Full… See the full description on the dataset page: https://huggingface.co/datasets/AxonData/french-call-center-speech-dataset.call-center-audio
Call Center Dataset
The datasets contain over 13,000+ hours of real-world conversations and feature 90%+ unique speakers. It is designed for advancing conversational AI and speech technologies. The dataset provides high-quality, time-stamped transcripts for model training in speech recognition and speaker diarization, enabling businesses to build and refine their AI systems.
By utilizing this dataset, researchers and developers can focus on analyzing customer interactions… See the full description on the dataset page: https://huggingface.co/datasets/UniDataPro/call-center-audio.Hindi_Call_Center_Audio_Dataset_Dual_ChannelDataset Description:
This dataset is a large-scale collection of 1,587,658 hours of processed Hindi dual-channel call center audio recordings, containing 3,569,083 hours of processed call center audio recordings across 54 languages, designed to support the development and training of advanced speech AI and conversational AI systems.
It consists of real-world customer and agent speech recordings collected from call center environments. The dataset is organized in a dual-channel format, where… See the full description on the dataset page: https://huggingface.co/datasets/InfoBayAI/Hindi_Call_Center_Audio_Dataset_Dual_Channel.Arabic-Call-Center-Audio-Dataset-Single-ChannelDataset Description:
This dataset is a large-scale collection of 64,027 hours of processed Arabic (AR) single-channel call center audio recordings, part of a broader multilingual conversational audio collection containing approximately 3,569,083 processed call center recordings across 54 languages, designed to support the development and training of advanced speech AI and conversational AI systems.
The dataset captures authentic speech characteristics such as tone variation, pauses, silence… See the full description on the dataset page: https://huggingface.co/datasets/InfoBayAI/Arabic-Call-Center-Audio-Dataset-Single-Channel.French_Call_Center_Audio_Dataset_Dual_ChannelDataset Description:
This dataset is a large-scale collection of 31,106 hours of processed French (FR) dual-channel call center audio recordings, containing 3,569,083 hours of processed call center audio recordings across 54 languages, designed to support the development and training of advanced speech AI and conversational AI systems.
It consists of real-world customer and agent speech recordings collected from call center environments. The dataset is organized in a dual-channel format, where… See the full description on the dataset page: https://huggingface.co/datasets/InfoBayAI/French_Call_Center_Audio_Dataset_Dual_Channel.Hindi-Call-Center-Audio-Dataset-Single-ChannelDataset Description:
This dataset is a large-scale collection of 1,587,658 hours of processed Hindi single-channel call center audio recordings, containing 3,569,083 hours of processed call center audio recordings across 54 languages, designed to support the development and training of advanced speech AI and conversational AI systems.
The dataset captures authentic speech characteristics such as tone variation, pauses, silence patterns, interruptions, and natural speaking behaviour commonly… See the full description on the dataset page: https://huggingface.co/datasets/InfoBayAI/Hindi-Call-Center-Audio-Dataset-Single-Channel.English_United_States_Call_Center_Audio_Dataset_Dual_ChannelDataset Description:
This dataset is a large-scale collection of 250,362 hours of processed English (US) dual-channel call center audio recordings, containing 3,569,083 hours of processed call center audio recordings across 54 languages, designed to support the development and training of advanced speech AI and conversational AI systems.
It consists of real-world customer and agent speech recordings collected from call center environments. The dataset is organized in a dual-channel format… See the full description on the dataset page: https://huggingface.co/datasets/InfoBayAI/English_United_States_Call_Center_Audio_Dataset_Dual_Channel.Filipino-Tagalog-Call-Center-Audio-Dataset-Single-ChannelDataset Description:
This dataset is a large-scale collection of 169 hours of processed Filipino (FIL) and 4019 hours of processed Tagalog (TL) single-channel call center audio recordings, containing 3,569,083 hours of processed call center audio recordings across 54 languages, designed to support the development and training of advanced speech AI and conversational AI systems.
The dataset captures authentic speech characteristics such as tone variation, pauses, silence patterns, and natural… See the full description on the dataset page: https://huggingface.co/datasets/InfoBayAI/Filipino-Tagalog-Call-Center-Audio-Dataset-Single-Channel.Arabic_Call_Center_Audio_Dataset_Dual_ChannelDataset Description:
This dataset is a large-scale collection of 64,027 hours of processed Arabic (AR) dual-channel call center audio recordings, containing 3,569,083 hours of processed call center audio recordings across 54 languages, designed to support the development and training of advanced speech AI and conversational AI systems.
It consists of real-world customer and agent speech recordings collected from call center environments. The dataset is organized in a dual-channel format, where… See the full description on the dataset page: https://huggingface.co/datasets/InfoBayAI/Arabic_Call_Center_Audio_Dataset_Dual_Channel.Russian_Call_Center_Audio_Dataset_Dual_ChannelDataset Description:
This dataset is a large-scale collection of 1,025 hours of processed Russian (RU) dual-channel call center audio recordings, containing 3,569,083 hours of processed call center audio recordings across 54 languages, designed to support the development and training of advanced speech AI and conversational AI systems.
It consists of real-world customer and agent speech recordings collected from call center environments. The dataset is organized in a dual-channel format, where… See the full description on the dataset page: https://huggingface.co/datasets/InfoBayAI/Russian_Call_Center_Audio_Dataset_Dual_Channel.English-United-Kingdom-Call-Center-Audio-Dataset-Single-ChannelDataset Description:
This dataset is a large-scale collection of 90,334 hours of processed English (UK) single-channel call center audio recordings, containing 3,569,083 hours of processed call center audio recordings across 54 languages, designed to support the development and training of advanced speech AI and conversational AI systems.
The dataset captures authentic speech characteristics such as tone variation, pauses, silence patterns, interruptions, and natural speaking behavior commonly… See the full description on the dataset page: https://huggingface.co/datasets/InfoBayAI/English-United-Kingdom-Call-Center-Audio-Dataset-Single-Channel.English_United_Kingdom_Call_Center_Audio_Dataset_Dual_ChannelDataset Description:
This dataset is a large-scale collection of 90,334 hours of processed English (UK) dual-channel call center audio recordings, containing 3,569,083 hours of processed call center audio recordings across 54 languages, designed to support the development and training of advanced speech AI and conversational AI systems.
It consists of real-world customer and agent speech recordings collected from call center environments. The dataset is organized in a dual-channel format… See the full description on the dataset page: https://huggingface.co/datasets/InfoBayAI/English_United_Kingdom_Call_Center_Audio_Dataset_Dual_Channel.Nepali_Call_Center_Audio_Dataset_Dual_ChannelDataset Description:
This dataset is a large-scale collection of 229,645 hours of processed Nepalese (NP) dual-channel call center audio recordings, containing 3,569,083 hours of processed call center audio recordings across 54 languages, designed to support the development and training of advanced speech AI and conversational AI systems.
It consists of real-world customer and agent speech recordings collected from call center environments. The dataset is organized in a dual-channel format… See the full description on the dataset page: https://huggingface.co/datasets/InfoBayAI/Nepali_Call_Center_Audio_Dataset_Dual_Channel.Marathi-Call-Center-Audio-Dataset-Single-ChannelDataset Description:
This dataset is a large-scale collection of 58,486 hours of processed Marathi (MR) single-channel call center audio recordings, containing 3,569,083 hours of processed call center audio recordings across 54 languages, designed to support the development and training of advanced speech AI and conversational AI systems.
The dataset captures authentic speech characteristics such as tone variation, pauses, silence patterns, and natural speaking behaviour commonly observed in… See the full description on the dataset page: https://huggingface.co/datasets/InfoBayAI/Marathi-Call-Center-Audio-Dataset-Single-Channel.Filipino_Tagalog_Call_Center_Audio_Dataset_Dual_ChannelDataset Description:
This dataset is a large-scale collection of 169 hours of processed Filipino (FIL) and 4,019 hours of processed Tagalog (TL) dual-channel call center audio recordings, containing 3,569,083 hours of processed call center audio recordings across 54 languages, designed to support the development and training of advanced speech AI and conversational AI systems.
It consists of real-world customer and agent speech recordings collected from call center environments. The dataset is… See the full description on the dataset page: https://huggingface.co/datasets/InfoBayAI/Filipino_Tagalog_Call_Center_Audio_Dataset_Dual_Channel.Odia_Call_Center_Audio_Dataset_Dual_ChannelDataset Description:
This dataset is a large-scale collection of 12,794 hours of processed Odia(Oriya) (OR) dual-channel call center audio recordings, containing 3,569,083 hours of processed call center audio recordings across 54 languages, designed to support the development and training of advanced speech AI and conversational AI systems.
It consists of real-world customer and agent speech recordings collected from call center environments. The dataset is organized in a dual-channel format… See the full description on the dataset page: https://huggingface.co/datasets/InfoBayAI/Odia_Call_Center_Audio_Dataset_Dual_Channel.English-role-playing-call-center-convers-different-moodsThis dataset features synthetic call center conversations in English, designed to reflect the diversity and complexity of real-world customer service interactions. It includes a broad range of global English accents and emotional tones, making it ideal for training robust conversational AI systems.
🌍 Accents Included: Indian, British (UK), American (USA), Chinese, and more.
🗣️ Speaker Diversity: Features speakers of different genders, age groups, and ethnic backgrounds, all freelancers based… See the full description on the dataset page: https://huggingface.co/datasets/AIxBlock/English-role-playing-call-center-convers-different-moods.German_Call_Center_Audio_Dataset_Dual_ChannelDataset Description:
This dataset is a large-scale collection of 212 hours of processed German (DE) dual-channel call center audio recordings, containing 3,569,083 hours of processed call center audio recordings across 54 languages, designed to support the development and training of advanced speech AI and conversational AI systems.
It consists of real-world customer and agent speech recordings collected from call center environments. The dataset is organized in a dual-channel format, where… See the full description on the dataset page: https://huggingface.co/datasets/InfoBayAI/German_Call_Center_Audio_Dataset_Dual_Channel.Russian-Call-Center-Audio-Dataset-Single-ChannelDataset Description:
This dataset is a large-scale collection of 1,025 hours of processed Russian (RU) single-channel call center audio recordings, containing 3,569,083 hours of processed call center audio recordings across 54 languages, designed to support the development and training of advanced speech AI and conversational AI systems.
The dataset captures authentic speech characteristics such as tone variation, pauses, silence patterns, and natural speaking behaviour commonly observed in… See the full description on the dataset page: https://huggingface.co/datasets/InfoBayAI/Russian-Call-Center-Audio-Dataset-Single-Channel.English_India_Call_Center_Audio_Dataset_Dual_ChannelDataset Description:
This dataset is a large-scale collection of 30,320 processed English (India) dual-channel call center audio recordings, part of a broader multilingual conversational audio collection containing approximately 3,569,083 processed call center recordings across 54 languages, designed to support the development and training of advanced speech AI and conversational AI systems.
It consists of real-world customer and agent speech recordings collected from call center environments.… See the full description on the dataset page: https://huggingface.co/datasets/InfoBayAI/English_India_Call_Center_Audio_Dataset_Dual_Channel.Mizo_Call_Center_Audio_Dataset_Dual_ChannelDataset Description:
This dataset is a large-scale collection of 468 hours of processed Mizo (MZ) dual-channel call center audio recordings, containing 3,569,083 hours of processed call center audio recordings across 54 languages, designed to support the development and training of advanced speech AI and conversational AI systems.
It consists of real-world customer and agent speech recordings collected from call center environments. The dataset is organized in a dual-channel format, where… See the full description on the dataset page: https://huggingface.co/datasets/InfoBayAI/Mizo_Call_Center_Audio_Dataset_Dual_Channel.Malayalam-Call-Center-Audio-Dataset-Single-ChannelDataset Description:
This dataset is a large-scale collection of 14,980 hours of processed Malayalam (ML) single-channel call center audio recordings, containing 3,569,083 hours of processed call center audio recordings across 54 languages, designed to support the development and training of advanced speech AI and conversational AI systems.
The dataset captures authentic speech characteristics such as tone variation, pauses, silence patterns, and natural speaking behaviour commonly observed in… See the full description on the dataset page: https://huggingface.co/datasets/InfoBayAI/Malayalam-Call-Center-Audio-Dataset-Single-Channel.