datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
Video2Reaction
Video2Reaction
Video2Reaction (V2R) is a multimodal dataset that maps short movie segments to the
distributional induced emotional reactions of viewers in the wild, as expressed through
social media comments. Unlike datasets that capture perceived emotion (the emotion
expressed by on-screen characters or filmmaker intent), Video2Reaction targets induced
emotion — the emotional response actually elicited in the audience — and represents each
clip's reaction as a probability… See the full description on the dataset page: https://huggingface.co/datasets/infofusionlab/Video2Reaction.infore2_audiobooks
unofficial mirror of InfoRe Technology public dataset №2
official announcement: https://www.facebook.com/groups/j2team.community/permalink/1010834009248719/
415h, 315k samples, vietnamese audiobooks of chinese wǔxiá 武俠 & xiānxiá 仙俠
bộ dữ liệu bóc ra từ YouTube đọc truyện võ hiệp & tiên hiệp, áp dụng kĩ thuật đối chiếu văn bản để dán nhãn tự động
official download:… See the full description on the dataset page: https://huggingface.co/datasets/doof-ferb/infore2_audiobooks.infore1_25hours
unofficial mirror of InfoRe Technology public dataset №1
official announcement: https://www.facebook.com/groups/j2team.community/permalink/1010834009248719/
25h, 14.9k samples, InfoRe paid a contractor to read text
official download: magnet:?xt=urn:btih:1cbe13fb14a390c852c016a924b4a5e879d85f41&dn=25hours.zip&tr=http%3A%2F%2Foffice.socials.vn%3A8725%2Fannounce
mirror: https://files.huylenguyen.com/datasets/infore/25hours.zip
unzip password: BroughtToYouByInfoRe
pre-process: see… See the full description on the dataset page: https://huggingface.co/datasets/doof-ferb/infore1_25hours.xtts-informal-frinfore25Arabic_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.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.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.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.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.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.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.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.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.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.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.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.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.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.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.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.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.Bengali_Call_Center_Audio_Dataset_Dual_ChannelDataset Description:
This dataset is a large-scale collection of 377,909 hours of processed Bengali (BN) 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/Bengali_Call_Center_Audio_Dataset_Dual_Channel.Spanish_Call_Center_Audio_Dataset_Dual_ChannelDataset Description:
This dataset is a large-scale collection of 452 hours of processed Spanish (MX) and 785 hours of processed Spanish (ES) 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/Spanish_Call_Center_Audio_Dataset_Dual_Channel.Somali-Call-Center-Audio-Dataset-Single-ChannelDataset Description:
This dataset is a large-scale collection of 952 hours of processed Somali (SO) and 105 hours of processed Somali (UG) 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/Somali-Call-Center-Audio-Dataset-Single-Channel.Swahili_Call_Center_Audio_Dataset_Dual_ChannelDataset Description:
This dataset is a large-scale collection of 194,331 hours of processed Swahili (SW) 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/Swahili_Call_Center_Audio_Dataset_Dual_Channel.Somali_Call_Center_Audio_Dataset_Dual_ChannelDataset Description:
This dataset is a large-scale collection of 952 hours of processed Somali (SO) and 105 hours of processed Somali (UG) 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/Somali_Call_Center_Audio_Dataset_Dual_Channel.Tamil_Call_Center_Audio_Dataset_Dual_ChannelDataset Description:
This dataset is a large-scale collection of 15,056 hours of processed Tamil (TA) 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/Tamil_Call_Center_Audio_Dataset_Dual_Channel.