19 datasets found
  1. Z

    Data from: TWIGMA: A dataset of AI-Generated Images with Metadata From...

    • data.niaid.nih.gov
    • zenodo.org
    Updated May 28, 2024
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    James Zou (2024). TWIGMA: A dataset of AI-Generated Images with Metadata From Twitter [Dataset]. https://data.niaid.nih.gov/resources?id=zenodo_8031784
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    Dataset updated
    May 28, 2024
    Dataset provided by
    Yiqun Chen
    James Zou
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    Update May 2024: Fixed a data type issue with "id" column that prevented twitter ids from rendering correctly.

    Recent progress in generative artificial intelligence (gen-AI) has enabled the generation of photo-realistic and artistically-inspiring photos at a single click, catering to millions of users online. To explore how people use gen-AI models such as DALLE and StableDiffusion, it is critical to understand the themes, contents, and variations present in the AI-generated photos. In this work, we introduce TWIGMA (TWItter Generative-ai images with MetadatA), a comprehensive dataset encompassing 800,000 gen-AI images collected from Jan 2021 to March 2023 on Twitter, with associated metadata (e.g., tweet text, creation date, number of likes).

    Through a comparative analysis of TWIGMA with natural images and human artwork, we find that gen-AI images possess distinctive characteristics and exhibit, on average, lower variability when compared to their non-gen-AI counterparts. Additionally, we find that the similarity between a gen-AI image and human images (i) is correlated with the number of likes; and (ii) can be used to identify human images that served as inspiration for the gen-AI creations. Finally, we observe a longitudinal shift in the themes of AI-generated images on Twitter, with users increasingly sharing artistically sophisticated content such as intricate human portraits, whereas their interest in simple subjects such as natural scenes and animals has decreased. Our analyses and findings underscore the significance of TWIGMA as a unique data resource for studying AI-generated images.

    Note that in accordance with the privacy and control policy of Twitter, NO raw content from Twitter is included in this dataset and users could and need to retrieve the original Twitter content used for analysis using the Twitter id. In addition, users who want to access Twitter data should consult and follow rules and regulations closely at the official Twitter developer policy at https://developer.twitter.com/en/developer-terms/policy.

  2. F

    General domain Human-Human conversation chats in Spanish

    • futurebeeai.com
    wav
    Updated Aug 1, 2022
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    FutureBee AI (2022). General domain Human-Human conversation chats in Spanish [Dataset]. https://www.futurebeeai.com/dataset/text-dataset/spanish-general-domain-conversation-text-dataset
    Explore at:
    wavAvailable download formats
    Dataset updated
    Aug 1, 2022
    Dataset provided by
    FutureBeeAI
    Authors
    FutureBee AI
    License

    https://www.futurebeeai.com/policies/ai-data-license-agreementhttps://www.futurebeeai.com/policies/ai-data-license-agreement

    Dataset funded by
    FutureBeeAI
    Description

    What’s Included

    This training dataset comprises more than 10,000 conversational text data between two native Spanish people in the general domain. We have a collection of chats on a variety of different topics/services/issues of daily life, such as music, books, festivals, health, kids, family, environment, study, childhood, cuisine, internet, movies, etc., and that makes the dataset diverse.

    These chats consist of language-specific words, and phrases and follow the native way of talking which makes the chats more information-rich for your NLP model. Apart from each chat being specific to the topic, it contains various attributes like people's names, addresses, contact information, email address, time, date, local currency, telephone numbers, local slang, etc too in various formats to make the text data unbiased.

    These chat scripts have between 300 and 700 words and up to 50 turns. 150 people that are a part of the FutureBeeAI crowd community contributed to this dataset. You will also receive chat metadata, such as participant age, gender, and country information, along with the chats. Dataset applications include conversational AI, natural language processing (NLP), smart assistants, text recognition, text analytics, and text prediction.

    This dataset is being expanded with new chats all the time. We are able to produce text data in a variety of languages to meet your unique requirements. Check out the FutureBeeAI community for a custom collection.

    This training dataset's licence belongs to FutureBeeAI!

  3. F

    General domain Human-Human conversation chats in Bahasa

    • futurebeeai.com
    wav
    Updated Aug 1, 2022
    + more versions
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    FutureBee AI (2022). General domain Human-Human conversation chats in Bahasa [Dataset]. https://www.futurebeeai.com/dataset/text-dataset/bahasa-general-domain-conversation-text-dataset
    Explore at:
    wavAvailable download formats
    Dataset updated
    Aug 1, 2022
    Dataset provided by
    FutureBeeAI
    Authors
    FutureBee AI
    License

    https://www.futurebeeai.com/policies/ai-data-license-agreementhttps://www.futurebeeai.com/policies/ai-data-license-agreement

    Dataset funded by
    FutureBeeAI
    Description

    What’s Included

    This training dataset comprises more than 10,000 conversational text data between two native Bahasa people in the general domain. We have a collection of chats on a variety of different topics/services/issues of daily life, such as music, books, festivals, health, kids, family, environment, study, childhood, cuisine, internet, movies, etc., and that makes the dataset diverse.

    These chats consist of language-specific words, and phrases and follow the native way of talking which makes the chats more information-rich for your NLP model. Apart from each chat being specific to the topic, it contains various attributes like people's names, addresses, contact information, email address, time, date, local currency, telephone numbers, local slang, etc too in various formats to make the text data unbiased.

    These chat scripts have between 300 and 700 words and up to 50 turns. 150 people that are a part of the FutureBeeAI crowd community contributed to this dataset. You will also receive chat metadata, such as participant age, gender, and country information, along with the chats. Dataset applications include conversational AI, natural language processing (NLP), smart assistants, text recognition, text analytics, and text prediction.

    This dataset is being expanded with new chats all the time. We are able to produce text data in a variety of languages to meet your unique requirements. Check out the FutureBeeAI community for a custom collection.

    This training dataset's licence belongs to FutureBeeAI!

  4. F

    General domain Human-Human conversation chats in Urdu

    • futurebeeai.com
    wav
    Updated Aug 1, 2022
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    FutureBee AI (2022). General domain Human-Human conversation chats in Urdu [Dataset]. https://www.futurebeeai.com/dataset/text-dataset/urdu-general-domain-conversation-text-dataset
    Explore at:
    wavAvailable download formats
    Dataset updated
    Aug 1, 2022
    Dataset provided by
    FutureBeeAI
    Authors
    FutureBee AI
    License

    https://www.futurebeeai.com/policies/ai-data-license-agreementhttps://www.futurebeeai.com/policies/ai-data-license-agreement

    Dataset funded by
    FutureBeeAI
    Description

    What’s Included

    This training dataset comprises more than 10,000 conversational text data between two native Urdu people in the general domain. We have a collection of chats on a variety of different topics/services/issues of daily life, such as music, books, festivals, health, kids, family, environment, study, childhood, cuisine, internet, movies, etc., and that makes the dataset diverse.

    These chats consist of language-specific words, and phrases and follow the native way of talking which makes the chats more information-rich for your NLP model. Apart from each chat being specific to the topic, it contains various attributes like people's names, addresses, contact information, email address, time, date, local currency, telephone numbers, local slang, etc too in various formats to make the text data unbiased.

    These chat scripts have between 300 and 700 words and up to 50 turns. 150 people that are a part of the FutureBeeAI crowd community contributed to this dataset. You will also receive chat metadata, such as participant age, gender, and country information, along with the chats. Dataset applications include conversational AI, natural language processing (NLP), smart assistants, text recognition, text analytics, and text prediction.

    This dataset is being expanded with new chats all the time. We are able to produce text data in a variety of languages to meet your unique requirements. Check out the FutureBeeAI community for a custom collection.

    This training dataset's licence belongs to FutureBeeAI!

  5. F

    General domain Human-Human conversation chats in German

    • futurebeeai.com
    wav
    Updated Aug 1, 2022
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    FutureBee AI (2022). General domain Human-Human conversation chats in German [Dataset]. https://www.futurebeeai.com/dataset/text-dataset/german-general-domain-conversation-text-dataset
    Explore at:
    wavAvailable download formats
    Dataset updated
    Aug 1, 2022
    Dataset provided by
    FutureBeeAI
    Authors
    FutureBee AI
    License

    https://www.futurebeeai.com/policies/ai-data-license-agreementhttps://www.futurebeeai.com/policies/ai-data-license-agreement

    Dataset funded by
    FutureBeeAI
    Description

    What’s Included

    This training dataset comprises more than 10,000 conversational text data between two native German people in the general domain. We have a collection of chats on a variety of different topics/services/issues of daily life, such as music, books, festivals, health, kids, family, environment, study, childhood, cuisine, internet, movies, etc., and that makes the dataset diverse.

    These chats consist of language-specific words, and phrases and follow the native way of talking which makes the chats more information-rich for your NLP model. Apart from each chat being specific to the topic, it contains various attributes like people's names, addresses, contact information, email address, time, date, local currency, telephone numbers, local slang, etc too in various formats to make the text data unbiased.

    These chat scripts have between 300 and 700 words and up to 50 turns. 150 people that are a part of the FutureBeeAI crowd community contributed to this dataset. You will also receive chat metadata, such as participant age, gender, and country information, along with the chats. Dataset applications include conversational AI, natural language processing (NLP), smart assistants, text recognition, text analytics, and text prediction.

    This dataset is being expanded with new chats all the time. We are able to produce text data in a variety of languages to meet your unique requirements. Check out the FutureBeeAI community for a custom collection.

    This training dataset's licence belongs to FutureBeeAI!

  6. F

    General domain Human-Human conversation chats in Bengali

    • futurebeeai.com
    wav
    Updated Aug 1, 2022
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    FutureBee AI (2022). General domain Human-Human conversation chats in Bengali [Dataset]. https://www.futurebeeai.com/dataset/text-dataset/bengali-general-domain-conversation-text-dataset
    Explore at:
    wavAvailable download formats
    Dataset updated
    Aug 1, 2022
    Dataset provided by
    FutureBeeAI
    Authors
    FutureBee AI
    License

    https://www.futurebeeai.com/policies/ai-data-license-agreementhttps://www.futurebeeai.com/policies/ai-data-license-agreement

    Dataset funded by
    FutureBeeAI
    Description

    What’s Included

    This training dataset comprises more than 10,000 conversational text data between two native Bengali people in the general domain. We have a collection of chats on a variety of different topics/services/issues of daily life, such as music, books, festivals, health, kids, family, environment, study, childhood, cuisine, internet, movies, etc., and that makes the dataset diverse.

    These chats consist of language-specific words, and phrases and follow the native way of talking which makes the chats more information-rich for your NLP model. Apart from each chat being specific to the topic, it contains various attributes like people's names, addresses, contact information, email address, time, date, local currency, telephone numbers, local slang, etc too in various formats to make the text data unbiased.

    These chat scripts have between 300 and 700 words and up to 50 turns. 150 people that are a part of the FutureBeeAI crowd community contributed to this dataset. You will also receive chat metadata, such as participant age, gender, and country information, along with the chats. Dataset applications include conversational AI, natural language processing (NLP), smart assistants, text recognition, text analytics, and text prediction.

    This dataset is being expanded with new chats all the time. We are able to produce text data in a variety of languages to meet your unique requirements. Check out the FutureBeeAI community for a custom collection.

    This training dataset's licence belongs to FutureBeeAI!

  7. F

    General domain Human-Human conversation chats in Punjabi

    • futurebeeai.com
    wav
    Updated Aug 1, 2022
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    FutureBee AI (2022). General domain Human-Human conversation chats in Punjabi [Dataset]. https://www.futurebeeai.com/dataset/text-dataset/punjabi-general-domain-conversation-text-dataset
    Explore at:
    wavAvailable download formats
    Dataset updated
    Aug 1, 2022
    Dataset provided by
    FutureBeeAI
    Authors
    FutureBee AI
    License

    https://www.futurebeeai.com/policies/ai-data-license-agreementhttps://www.futurebeeai.com/policies/ai-data-license-agreement

    Dataset funded by
    FutureBeeAI
    Description

    What’s Included

    This training dataset comprises more than 10,000 conversational text data between two native Punjabi people in the general domain. We have a collection of chats on a variety of different topics/services/issues of daily life, such as music, books, festivals, health, kids, family, environment, study, childhood, cuisine, internet, movies, etc., and that makes the dataset diverse.

    These chats consist of language-specific words, and phrases and follow the native way of talking which makes the chats more information-rich for your NLP model. Apart from each chat being specific to the topic, it contains various attributes like people's names, addresses, contact information, email address, time, date, local currency, telephone numbers, local slang, etc too in various formats to make the text data unbiased.

    These chat scripts have between 300 and 700 words and up to 50 turns. 150 people that are a part of the FutureBeeAI crowd community contributed to this dataset. You will also receive chat metadata, such as participant age, gender, and country information, along with the chats. Dataset applications include conversational AI, natural language processing (NLP), smart assistants, text recognition, text analytics, and text prediction.

    This dataset is being expanded with new chats all the time. We are able to produce text data in a variety of languages to meet your unique requirements. Check out the FutureBeeAI community for a custom collection.

    This training dataset's licence belongs to FutureBeeAI!

  8. F

    Colombian Spanish General Conversation Speech Dataset for ASR

    • futurebeeai.com
    wav
    Updated Aug 1, 2022
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    FutureBee AI (2022). Colombian Spanish General Conversation Speech Dataset for ASR [Dataset]. https://www.futurebeeai.com/dataset/speech-dataset/general-conversation-spanish-colombia
    Explore at:
    wavAvailable download formats
    Dataset updated
    Aug 1, 2022
    Dataset provided by
    FutureBeeAI
    Authors
    FutureBee AI
    License

    https://www.futurebeeai.com/policies/ai-data-license-agreementhttps://www.futurebeeai.com/policies/ai-data-license-agreement

    Dataset funded by
    FutureBeeAI
    Description

    Introduction

    Welcome to the Colombian Spanish General Conversation Speech Dataset — a rich, linguistically diverse corpus purpose-built to accelerate the development of Spanish speech technologies. This dataset is designed to train and fine-tune ASR systems, spoken language understanding models, and generative voice AI tailored to real-world Colombian Spanish communication.

    Curated by FutureBeeAI, this 30 hours dataset offers unscripted, spontaneous two-speaker conversations across a wide array of real-life topics. It enables researchers, AI developers, and voice-first product teams to build robust, production-grade Spanish speech models that understand and respond to authentic Colombian accents and dialects.

    Speech Data

    The dataset comprises 30 hours of high-quality audio, featuring natural, free-flowing dialogue between native speakers of Colombian Spanish. These sessions range from informal daily talks to deeper, topic-specific discussions, ensuring variability and context richness for diverse use cases.

    Participant Diversity:
    Speakers: 60 verified native Colombian Spanish speakers from FutureBeeAI’s contributor community.
    Regions: Representing various provinces of Colombia to ensure dialectal diversity and demographic balance.
    Demographics: A balanced gender ratio (60% male, 40% female) with participant ages ranging from 18 to 70 years.
    Recording Details:
    Conversation Style: Unscripted, spontaneous peer-to-peer dialogues.
    Duration: Each conversation ranges from 15 to 60 minutes.
    Audio Format: Stereo WAV files, 16-bit depth, recorded at 16kHz sample rate.
    Environment: Quiet, echo-free settings with no background noise.

    Topic Diversity

    The dataset spans a wide variety of everyday and domain-relevant themes. This topic diversity ensures the resulting models are adaptable to broad speech contexts.

    Sample Topics Include:
    Family & Relationships
    Food & Recipes
    Education & Career
    Healthcare Discussions
    Social Issues
    Technology & Gadgets
    Travel & Local Culture
    Shopping & Marketplace Experiences, and many more.

    Transcription

    Each audio file is paired with a human-verified, verbatim transcription available in JSON format.

    Transcription Highlights:
    Speaker-segmented dialogues
    Time-coded utterances
    Non-speech elements (pauses, laughter, etc.)
    High transcription accuracy, achieved through double QA pass, average WER < 5%

    These transcriptions are production-ready, enabling seamless integration into ASR model pipelines or conversational AI workflows.

    Metadata

    The dataset comes with granular metadata for both speakers and recordings:

    Speaker Metadata: Age, gender, accent, dialect, state/province, and participant ID.
    Recording Metadata: Topic, duration, audio format, device type, and sample rate.

    Such metadata helps developers fine-tune model training and supports use-case-specific filtering or demographic analysis.

    Usage and Applications

    This dataset is a versatile resource for multiple Spanish speech and language AI applications:

    ASR Development: Train accurate speech-to-text systems for Colombian Spanish.
    Voice Assistants: Build smart assistants capable of understanding natural Colombian conversations.
    <div style="margin-top:10px; margin-bottom: 10px; padding-left: 30px; display: flex;

  9. F

    General domain Human-Human conversation chats in Korean

    • futurebeeai.com
    wav
    Updated Aug 1, 2022
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    FutureBee AI (2022). General domain Human-Human conversation chats in Korean [Dataset]. https://www.futurebeeai.com/dataset/text-dataset/korean-general-domain-conversation-text-dataset
    Explore at:
    wavAvailable download formats
    Dataset updated
    Aug 1, 2022
    Dataset provided by
    FutureBeeAI
    Authors
    FutureBee AI
    License

    https://www.futurebeeai.com/policies/ai-data-license-agreementhttps://www.futurebeeai.com/policies/ai-data-license-agreement

    Dataset funded by
    FutureBeeAI
    Description

    What’s Included

    This training dataset comprises more than 10,000 conversational text data between two native Korean people in the general domain. We have a collection of chats on a variety of different topics/services/issues of daily life, such as music, books, festivals, health, kids, family, environment, study, childhood, cuisine, internet, movies, etc., and that makes the dataset diverse.

    These chats consist of language-specific words, and phrases and follow the native way of talking which makes the chats more information-rich for your NLP model. Apart from each chat being specific to the topic, it contains various attributes like people's names, addresses, contact information, email address, time, date, local currency, telephone numbers, local slang, etc too in various formats to make the text data unbiased.

    These chat scripts have between 300 and 700 words and up to 50 turns. 150 people that are a part of the FutureBeeAI crowd community contributed to this dataset. You will also receive chat metadata, such as participant age, gender, and country information, along with the chats. Dataset applications include conversational AI, natural language processing (NLP), smart assistants, text recognition, text analytics, and text prediction.

    This dataset is being expanded with new chats all the time. We are able to produce text data in a variety of languages to meet your unique requirements. Check out the FutureBeeAI community for a custom collection.

    This training dataset's licence belongs to FutureBeeAI!

  10. F

    General domain Human-Human conversation chats in Turkish

    • futurebeeai.com
    wav
    Updated Aug 1, 2022
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    FutureBee AI (2022). General domain Human-Human conversation chats in Turkish [Dataset]. https://www.futurebeeai.com/dataset/text-dataset/turkish-general-domain-conversation-text-dataset
    Explore at:
    wavAvailable download formats
    Dataset updated
    Aug 1, 2022
    Dataset provided by
    FutureBeeAI
    Authors
    FutureBee AI
    License

    https://www.futurebeeai.com/policies/ai-data-license-agreementhttps://www.futurebeeai.com/policies/ai-data-license-agreement

    Dataset funded by
    FutureBeeAI
    Description

    What’s Included

    This training dataset comprises more than 10,000 conversational text data between two native Turkish people in the general domain. We have a collection of chats on a variety of different topics/services/issues of daily life, such as music, books, festivals, health, kids, family, environment, study, childhood, cuisine, internet, movies, etc., and that makes the dataset diverse.

    These chats consist of language-specific words, and phrases and follow the native way of talking which makes the chats more information-rich for your NLP model. Apart from each chat being specific to the topic, it contains various attributes like people's names, addresses, contact information, email address, time, date, local currency, telephone numbers, local slang, etc too in various formats to make the text data unbiased.

    These chat scripts have between 300 and 700 words and up to 50 turns. 150 people that are a part of the FutureBeeAI crowd community contributed to this dataset. You will also receive chat metadata, such as participant age, gender, and country information, along with the chats. Dataset applications include conversational AI, natural language processing (NLP), smart assistants, text recognition, text analytics, and text prediction.

    This dataset is being expanded with new chats all the time. We are able to produce text data in a variety of languages to meet your unique requirements. Check out the FutureBeeAI community for a custom collection.

    This training dataset's licence belongs to FutureBeeAI!

  11. F

    Mexican Spanish General Conversation Speech Dataset for ASR

    • futurebeeai.com
    wav
    Updated Aug 1, 2022
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    FutureBee AI (2022). Mexican Spanish General Conversation Speech Dataset for ASR [Dataset]. https://www.futurebeeai.com/dataset/speech-dataset/general-conversation-spanish-mexico
    Explore at:
    wavAvailable download formats
    Dataset updated
    Aug 1, 2022
    Dataset provided by
    FutureBeeAI
    Authors
    FutureBee AI
    License

    https://www.futurebeeai.com/policies/ai-data-license-agreementhttps://www.futurebeeai.com/policies/ai-data-license-agreement

    Area covered
    Mexico
    Dataset funded by
    FutureBeeAI
    Description

    Introduction

    Welcome to the Mexican Spanish General Conversation Speech Dataset — a rich, linguistically diverse corpus purpose-built to accelerate the development of Spanish speech technologies. This dataset is designed to train and fine-tune ASR systems, spoken language understanding models, and generative voice AI tailored to real-world Mexican Spanish communication.

    Curated by FutureBeeAI, this 30 hours dataset offers unscripted, spontaneous two-speaker conversations across a wide array of real-life topics. It enables researchers, AI developers, and voice-first product teams to build robust, production-grade Spanish speech models that understand and respond to authentic Mexican accents and dialects.

    Speech Data

    The dataset comprises 30 hours of high-quality audio, featuring natural, free-flowing dialogue between native speakers of Mexican Spanish. These sessions range from informal daily talks to deeper, topic-specific discussions, ensuring variability and context richness for diverse use cases.

    Participant Diversity:
    Speakers: 60 verified native Mexican Spanish speakers from FutureBeeAI’s contributor community.
    Regions: Representing various provinces of Mexico to ensure dialectal diversity and demographic balance.
    Demographics: A balanced gender ratio (60% male, 40% female) with participant ages ranging from 18 to 70 years.
    Recording Details:
    Conversation Style: Unscripted, spontaneous peer-to-peer dialogues.
    Duration: Each conversation ranges from 15 to 60 minutes.
    Audio Format: Stereo WAV files, 16-bit depth, recorded at 16kHz sample rate.
    Environment: Quiet, echo-free settings with no background noise.

    Topic Diversity

    The dataset spans a wide variety of everyday and domain-relevant themes. This topic diversity ensures the resulting models are adaptable to broad speech contexts.

    Sample Topics Include:
    Family & Relationships
    Food & Recipes
    Education & Career
    Healthcare Discussions
    Social Issues
    Technology & Gadgets
    Travel & Local Culture
    Shopping & Marketplace Experiences, and many more.

    Transcription

    Each audio file is paired with a human-verified, verbatim transcription available in JSON format.

    Transcription Highlights:
    Speaker-segmented dialogues
    Time-coded utterances
    Non-speech elements (pauses, laughter, etc.)
    High transcription accuracy, achieved through double QA pass, average WER < 5%

    These transcriptions are production-ready, enabling seamless integration into ASR model pipelines or conversational AI workflows.

    Metadata

    The dataset comes with granular metadata for both speakers and recordings:

    Speaker Metadata: Age, gender, accent, dialect, state/province, and participant ID.
    Recording Metadata: Topic, duration, audio format, device type, and sample rate.

    Such metadata helps developers fine-tune model training and supports use-case-specific filtering or demographic analysis.

    Usage and Applications

    This dataset is a versatile resource for multiple Spanish speech and language AI applications:

    ASR Development: Train accurate speech-to-text systems for Mexican Spanish.
    Voice Assistants: Build smart assistants capable of understanding natural Mexican conversations.
    <div style="margin-top:10px; margin-bottom: 10px; padding-left: 30px; display: flex; gap: 16px;

  12. F

    General domain Human-Human conversation chats in Chinese

    • futurebeeai.com
    wav
    Updated Aug 1, 2022
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    FutureBee AI (2022). General domain Human-Human conversation chats in Chinese [Dataset]. https://www.futurebeeai.com/dataset/text-dataset/chinese-general-domain-conversation-text-dataset
    Explore at:
    wavAvailable download formats
    Dataset updated
    Aug 1, 2022
    Dataset provided by
    FutureBeeAI
    Authors
    FutureBee AI
    License

    https://www.futurebeeai.com/policies/ai-data-license-agreementhttps://www.futurebeeai.com/policies/ai-data-license-agreement

    Dataset funded by
    FutureBeeAI
    Description

    What’s Included

    This training dataset comprises more than 10,000 conversational text data between two native Chinese people in the general domain. We have a collection of chats on a variety of different topics/services/issues of daily life, such as music, books, festivals, health, kids, family, environment, study, childhood, cuisine, internet, movies, etc., and that makes the dataset diverse.

    These chats consist of language-specific words, and phrases and follow the native way of talking which makes the chats more information-rich for your NLP model. Apart from each chat being specific to the topic, it contains various attributes like people's names, addresses, contact information, email address, time, date, local currency, telephone numbers, local slang, etc too in various formats to make the text data unbiased.

    These chat scripts have between 300 and 700 words and up to 50 turns. 150 people that are a part of the FutureBeeAI crowd community contributed to this dataset. You will also receive chat metadata, such as participant age, gender, and country information, along with the chats. Dataset applications include conversational AI, natural language processing (NLP), smart assistants, text recognition, text analytics, and text prediction.

    This dataset is being expanded with new chats all the time. We are able to produce text data in a variety of languages to meet your unique requirements. Check out the FutureBeeAI community for a custom collection.

    This training dataset's licence belongs to FutureBeeAI!

  13. F

    American English General Conversation Speech Dataset for ASR

    • futurebeeai.com
    wav
    Updated Aug 1, 2022
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    FutureBee AI (2022). American English General Conversation Speech Dataset for ASR [Dataset]. https://www.futurebeeai.com/dataset/speech-dataset/general-conversation-english-usa
    Explore at:
    wavAvailable download formats
    Dataset updated
    Aug 1, 2022
    Dataset provided by
    FutureBeeAI
    Authors
    FutureBee AI
    License

    https://www.futurebeeai.com/policies/ai-data-license-agreementhttps://www.futurebeeai.com/policies/ai-data-license-agreement

    Area covered
    United States
    Dataset funded by
    FutureBeeAI
    Description

    Introduction

    Welcome to the US English General Conversation Speech Dataset — a rich, linguistically diverse corpus purpose-built to accelerate the development of English speech technologies. This dataset is designed to train and fine-tune ASR systems, spoken language understanding models, and generative voice AI tailored to real-world US English communication.

    Curated by FutureBeeAI, this 30 hours dataset offers unscripted, spontaneous two-speaker conversations across a wide array of real-life topics. It enables researchers, AI developers, and voice-first product teams to build robust, production-grade English speech models that understand and respond to authentic American accents and dialects.

    Speech Data

    The dataset comprises 30 hours of high-quality audio, featuring natural, free-flowing dialogue between native speakers of US English. These sessions range from informal daily talks to deeper, topic-specific discussions, ensuring variability and context richness for diverse use cases.

    Participant Diversity:
    Speakers: 60 verified native US English speakers from FutureBeeAI’s contributor community.
    Regions: Representing various provinces of United States of America to ensure dialectal diversity and demographic balance.
    Demographics: A balanced gender ratio (60% male, 40% female) with participant ages ranging from 18 to 70 years.
    Recording Details:
    Conversation Style: Unscripted, spontaneous peer-to-peer dialogues.
    Duration: Each conversation ranges from 15 to 60 minutes.
    Audio Format: Stereo WAV files, 16-bit depth, recorded at 16kHz sample rate.
    Environment: Quiet, echo-free settings with no background noise.

    Topic Diversity

    The dataset spans a wide variety of everyday and domain-relevant themes. This topic diversity ensures the resulting models are adaptable to broad speech contexts.

    Sample Topics Include:
    Family & Relationships
    Food & Recipes
    Education & Career
    Healthcare Discussions
    Social Issues
    Technology & Gadgets
    Travel & Local Culture
    Shopping & Marketplace Experiences, and many more.

    Transcription

    Each audio file is paired with a human-verified, verbatim transcription available in JSON format.

    Transcription Highlights:
    Speaker-segmented dialogues
    Time-coded utterances
    Non-speech elements (pauses, laughter, etc.)
    High transcription accuracy, achieved through double QA pass, average WER < 5%

    These transcriptions are production-ready, enabling seamless integration into ASR model pipelines or conversational AI workflows.

    Metadata

    The dataset comes with granular metadata for both speakers and recordings:

    Speaker Metadata: Age, gender, accent, dialect, state/province, and participant ID.
    Recording Metadata: Topic, duration, audio format, device type, and sample rate.

    Such metadata helps developers fine-tune model training and supports use-case-specific filtering or demographic analysis.

    Usage and Applications

    This dataset is a versatile resource for multiple English speech and language AI applications:

    ASR Development: Train accurate speech-to-text systems for US English.
    Voice Assistants: Build smart assistants capable of understanding natural American conversations.
    <div style="margin-top:10px; margin-bottom: 10px; padding-left: 30px; display: flex; gap: 16px; align-items:

  14. F

    Norwegian General Conversation Speech Dataset for ASR

    • futurebeeai.com
    wav
    Updated Aug 1, 2022
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    FutureBee AI (2022). Norwegian General Conversation Speech Dataset for ASR [Dataset]. https://www.futurebeeai.com/dataset/speech-dataset/general-conversation-norwegian-norway
    Explore at:
    wavAvailable download formats
    Dataset updated
    Aug 1, 2022
    Dataset provided by
    FutureBeeAI
    Authors
    FutureBee AI
    License

    https://www.futurebeeai.com/policies/ai-data-license-agreementhttps://www.futurebeeai.com/policies/ai-data-license-agreement

    Dataset funded by
    FutureBeeAI
    Description

    Introduction

    Welcome to the Norwegian General Conversation Speech Dataset — a rich, linguistically diverse corpus purpose-built to accelerate the development of Norwegian speech technologies. This dataset is designed to train and fine-tune ASR systems, spoken language understanding models, and generative voice AI tailored to real-world Norwegian communication.

    Curated by FutureBeeAI, this 30 hours dataset offers unscripted, spontaneous two-speaker conversations across a wide array of real-life topics. It enables researchers, AI developers, and voice-first product teams to build robust, production-grade Norwegian speech models that understand and respond to authentic Norwegian accents and dialects.

    Speech Data

    The dataset comprises 30 hours of high-quality audio, featuring natural, free-flowing dialogue between native speakers of Norwegian. These sessions range from informal daily talks to deeper, topic-specific discussions, ensuring variability and context richness for diverse use cases.

    Participant Diversity:
    Speakers: 60 verified native Norwegian speakers from FutureBeeAI’s contributor community.
    Regions: Representing various provinces of Norway to ensure dialectal diversity and demographic balance.
    Demographics: A balanced gender ratio (60% male, 40% female) with participant ages ranging from 18 to 70 years.
    Recording Details:
    Conversation Style: Unscripted, spontaneous peer-to-peer dialogues.
    Duration: Each conversation ranges from 15 to 60 minutes.
    Audio Format: Stereo WAV files, 16-bit depth, recorded at 16kHz sample rate.
    Environment: Quiet, echo-free settings with no background noise.

    Topic Diversity

    The dataset spans a wide variety of everyday and domain-relevant themes. This topic diversity ensures the resulting models are adaptable to broad speech contexts.

    Sample Topics Include:
    Family & Relationships
    Food & Recipes
    Education & Career
    Healthcare Discussions
    Social Issues
    Technology & Gadgets
    Travel & Local Culture
    Shopping & Marketplace Experiences, and many more.

    Transcription

    Each audio file is paired with a human-verified, verbatim transcription available in JSON format.

    Transcription Highlights:
    Speaker-segmented dialogues
    Time-coded utterances
    Non-speech elements (pauses, laughter, etc.)
    High transcription accuracy, achieved through double QA pass, average WER < 5%

    These transcriptions are production-ready, enabling seamless integration into ASR model pipelines or conversational AI workflows.

    Metadata

    The dataset comes with granular metadata for both speakers and recordings:

    Speaker Metadata: Age, gender, accent, dialect, state/province, and participant ID.
    Recording Metadata: Topic, duration, audio format, device type, and sample rate.

    Such metadata helps developers fine-tune model training and supports use-case-specific filtering or demographic analysis.

    Usage and Applications

    This dataset is a versatile resource for multiple Norwegian speech and language AI applications:

    ASR Development: Train accurate speech-to-text systems for Norwegian.
    Voice Assistants: Build smart assistants capable of understanding natural Norwegian conversations.

  15. F

    General domain Human-Human conversation chats in Marathi

    • futurebeeai.com
    wav
    Updated Aug 1, 2022
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    FutureBee AI (2022). General domain Human-Human conversation chats in Marathi [Dataset]. https://www.futurebeeai.com/dataset/text-dataset/marathi-general-domain-conversation-text-dataset
    Explore at:
    wavAvailable download formats
    Dataset updated
    Aug 1, 2022
    Dataset provided by
    FutureBeeAI
    Authors
    FutureBee AI
    License

    https://www.futurebeeai.com/policies/ai-data-license-agreementhttps://www.futurebeeai.com/policies/ai-data-license-agreement

    Dataset funded by
    FutureBeeAI
    Description

    What’s Included

    This training dataset comprises more than 10,000 conversational text data between two native Marathi people in the general domain. We have a collection of chats on a variety of different topics/services/issues of daily life, such as music, books, festivals, health, kids, family, environment, study, childhood, cuisine, internet, movies, etc., and that makes the dataset diverse.

    These chats consist of language-specific words, and phrases and follow the native way of talking which makes the chats more information-rich for your NLP model. Apart from each chat being specific to the topic, it contains various attributes like people's names, addresses, contact information, email address, time, date, local currency, telephone numbers, local slang, etc too in various formats to make the text data unbiased.

    These chat scripts have between 300 and 700 words and up to 50 turns. 150 people that are a part of the FutureBeeAI crowd community contributed to this dataset. You will also receive chat metadata, such as participant age, gender, and country information, along with the chats. Dataset applications include conversational AI, natural language processing (NLP), smart assistants, text recognition, text analytics, and text prediction.

    This dataset is being expanded with new chats all the time. We are able to produce text data in a variety of languages to meet your unique requirements. Check out the FutureBeeAI community for a custom collection.

    This training dataset's licence belongs to FutureBeeAI!

  16. F

    General domain Human-Human conversation chats in Dutch

    • futurebeeai.com
    wav
    Updated Aug 1, 2022
    Share
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    FutureBee AI (2022). General domain Human-Human conversation chats in Dutch [Dataset]. https://www.futurebeeai.com/dataset/text-dataset/dutch-general-domain-conversation-text-dataset
    Explore at:
    wavAvailable download formats
    Dataset updated
    Aug 1, 2022
    Dataset provided by
    FutureBeeAI
    Authors
    FutureBee AI
    License

    https://www.futurebeeai.com/policies/ai-data-license-agreementhttps://www.futurebeeai.com/policies/ai-data-license-agreement

    Dataset funded by
    FutureBeeAI
    Description

    What’s Included

    This training dataset comprises more than 10,000 conversational text data between two native Dutch people in the general domain. We have a collection of chats on a variety of different topics/services/issues of daily life, such as music, books, festivals, health, kids, family, environment, study, childhood, cuisine, internet, movies, etc., and that makes the dataset diverse.

    These chats consist of language-specific words, and phrases and follow the native way of talking which makes the chats more information-rich for your NLP model. Apart from each chat being specific to the topic, it contains various attributes like people's names, addresses, contact information, email address, time, date, local currency, telephone numbers, local slang, etc too in various formats to make the text data unbiased.

    These chat scripts have between 300 and 700 words and up to 50 turns. 150 people that are a part of the FutureBeeAI crowd community contributed to this dataset. You will also receive chat metadata, such as participant age, gender, and country information, along with the chats. Dataset applications include conversational AI, natural language processing (NLP), smart assistants, text recognition, text analytics, and text prediction.

    This dataset is being expanded with new chats all the time. We are able to produce text data in a variety of languages to meet your unique requirements. Check out the FutureBeeAI community for a custom collection.

    This training dataset's licence belongs to FutureBeeAI!

  17. F

    Spanish(Spain) General Conversation Speech Dataset for ASR

    • futurebeeai.com
    wav
    Updated Aug 1, 2022
    Share
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    FutureBee AI (2022). Spanish(Spain) General Conversation Speech Dataset for ASR [Dataset]. https://www.futurebeeai.com/dataset/speech-dataset/general-conversation-spanish-spain
    Explore at:
    wavAvailable download formats
    Dataset updated
    Aug 1, 2022
    Dataset provided by
    FutureBeeAI
    Authors
    FutureBee AI
    License

    https://www.futurebeeai.com/policies/ai-data-license-agreementhttps://www.futurebeeai.com/policies/ai-data-license-agreement

    Area covered
    Spain
    Dataset funded by
    FutureBeeAI
    Description

    Introduction

    Welcome to the Spanish General Conversation Speech Dataset — a rich, linguistically diverse corpus purpose-built to accelerate the development of Spanish speech technologies. This dataset is designed to train and fine-tune ASR systems, spoken language understanding models, and generative voice AI tailored to real-world Spanish communication.

    Curated by FutureBeeAI, this 30 hours dataset offers unscripted, spontaneous two-speaker conversations across a wide array of real-life topics. It enables researchers, AI developers, and voice-first product teams to build robust, production-grade Spanish speech models that understand and respond to authentic Spanish accents and dialects.

    Speech Data

    The dataset comprises 30 hours of high-quality audio, featuring natural, free-flowing dialogue between native speakers of Spanish. These sessions range from informal daily talks to deeper, topic-specific discussions, ensuring variability and context richness for diverse use cases.

    Participant Diversity:
    Speakers: 60 verified native Spanish speakers from FutureBeeAI’s contributor community.
    Regions: Representing various provinces of Spain to ensure dialectal diversity and demographic balance.
    Demographics: A balanced gender ratio (60% male, 40% female) with participant ages ranging from 18 to 70 years.
    Recording Details:
    Conversation Style: Unscripted, spontaneous peer-to-peer dialogues.
    Duration: Each conversation ranges from 15 to 60 minutes.
    Audio Format: Stereo WAV files, 16-bit depth, recorded at 16kHz sample rate.
    Environment: Quiet, echo-free settings with no background noise.

    Topic Diversity

    The dataset spans a wide variety of everyday and domain-relevant themes. This topic diversity ensures the resulting models are adaptable to broad speech contexts.

    Sample Topics Include:
    Family & Relationships
    Food & Recipes
    Education & Career
    Healthcare Discussions
    Social Issues
    Technology & Gadgets
    Travel & Local Culture
    Shopping & Marketplace Experiences, and many more.

    Transcription

    Each audio file is paired with a human-verified, verbatim transcription available in JSON format.

    Transcription Highlights:
    Speaker-segmented dialogues
    Time-coded utterances
    Non-speech elements (pauses, laughter, etc.)
    High transcription accuracy, achieved through double QA pass, average WER < 5%

    These transcriptions are production-ready, enabling seamless integration into ASR model pipelines or conversational AI workflows.

    Metadata

    The dataset comes with granular metadata for both speakers and recordings:

    Speaker Metadata: Age, gender, accent, dialect, state/province, and participant ID.
    Recording Metadata: Topic, duration, audio format, device type, and sample rate.

    Such metadata helps developers fine-tune model training and supports use-case-specific filtering or demographic analysis.

    Usage and Applications

    This dataset is a versatile resource for multiple Spanish speech and language AI applications:

    ASR Development: Train accurate speech-to-text systems for Spanish.
    Voice Assistants: Build smart assistants capable of understanding natural Spanish conversations.
    <span

  18. F

    General domain Human-Human conversation chats in Ukrainian

    • futurebeeai.com
    wav
    Updated Aug 1, 2022
    Share
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    FutureBee AI (2022). General domain Human-Human conversation chats in Ukrainian [Dataset]. https://www.futurebeeai.com/dataset/text-dataset/ukrainian-general-domain-conversation-text-dataset
    Explore at:
    wavAvailable download formats
    Dataset updated
    Aug 1, 2022
    Dataset provided by
    FutureBeeAI
    Authors
    FutureBee AI
    License

    https://www.futurebeeai.com/policies/ai-data-license-agreementhttps://www.futurebeeai.com/policies/ai-data-license-agreement

    Area covered
    Ukraine
    Dataset funded by
    FutureBeeAI
    Description

    What’s Included

    This training dataset comprises more than 10,000 conversational text data between two native Ukrainian people in the general domain. We have a collection of chats on a variety of different topics/services/issues of daily life, such as music, books, festivals, health, kids, family, environment, study, childhood, cuisine, internet, movies, etc., and that makes the dataset diverse.

    These chats consist of language-specific words, and phrases and follow the native way of talking which makes the chats more information-rich for your NLP model. Apart from each chat being specific to the topic, it contains various attributes like people's names, addresses, contact information, email address, time, date, local currency, telephone numbers, local slang, etc too in various formats to make the text data unbiased.

    These chat scripts have between 300 and 700 words and up to 50 turns. 150 people that are a part of the FutureBeeAI crowd community contributed to this dataset. You will also receive chat metadata, such as participant age, gender, and country information, along with the chats. Dataset applications include conversational AI, natural language processing (NLP), smart assistants, text recognition, text analytics, and text prediction.

    This dataset is being expanded with new chats all the time. We are able to produce text data in a variety of languages to meet your unique requirements. Check out the FutureBeeAI community for a custom collection.

    This training dataset's licence belongs to FutureBeeAI!

  19. F

    General domain Human-Human conversation chats in Norwegian

    • futurebeeai.com
    wav
    Updated Aug 1, 2022
    Share
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    Click to copy link
    Link copied
    Close
    Cite
    FutureBee AI (2022). General domain Human-Human conversation chats in Norwegian [Dataset]. https://www.futurebeeai.com/dataset/text-dataset/norwegian-general-domain-conversation-text-dataset
    Explore at:
    wavAvailable download formats
    Dataset updated
    Aug 1, 2022
    Dataset provided by
    FutureBeeAI
    Authors
    FutureBee AI
    License

    https://www.futurebeeai.com/policies/ai-data-license-agreementhttps://www.futurebeeai.com/policies/ai-data-license-agreement

    Dataset funded by
    FutureBeeAI
    Description

    What’s Included

    This training dataset comprises more than 10,000 conversational text data between two native Norwegian people in the general domain. We have a collection of chats on a variety of different topics/services/issues of daily life, such as music, books, festivals, health, kids, family, environment, study, childhood, cuisine, internet, movies, etc., and that makes the dataset diverse.

    These chats consist of language-specific words, and phrases and follow the native way of talking which makes the chats more information-rich for your NLP model. Apart from each chat being specific to the topic, it contains various attributes like people's names, addresses, contact information, email address, time, date, local currency, telephone numbers, local slang, etc too in various formats to make the text data unbiased.

    These chat scripts have between 300 and 700 words and up to 50 turns. 150 people that are a part of the FutureBeeAI crowd community contributed to this dataset. You will also receive chat metadata, such as participant age, gender, and country information, along with the chats. Dataset applications include conversational AI, natural language processing (NLP), smart assistants, text recognition, text analytics, and text prediction.

    This dataset is being expanded with new chats all the time. We are able to produce text data in a variety of languages to meet your unique requirements. Check out the FutureBeeAI community for a custom collection.

    This training dataset's licence belongs to FutureBeeAI!

  20. Not seeing a result you expected?
    Learn how you can add new datasets to our index.

Share
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James Zou (2024). TWIGMA: A dataset of AI-Generated Images with Metadata From Twitter [Dataset]. https://data.niaid.nih.gov/resources?id=zenodo_8031784

Data from: TWIGMA: A dataset of AI-Generated Images with Metadata From Twitter

Related Article
Explore at:
Dataset updated
May 28, 2024
Dataset provided by
Yiqun Chen
James Zou
License

Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically

Description

Update May 2024: Fixed a data type issue with "id" column that prevented twitter ids from rendering correctly.

Recent progress in generative artificial intelligence (gen-AI) has enabled the generation of photo-realistic and artistically-inspiring photos at a single click, catering to millions of users online. To explore how people use gen-AI models such as DALLE and StableDiffusion, it is critical to understand the themes, contents, and variations present in the AI-generated photos. In this work, we introduce TWIGMA (TWItter Generative-ai images with MetadatA), a comprehensive dataset encompassing 800,000 gen-AI images collected from Jan 2021 to March 2023 on Twitter, with associated metadata (e.g., tweet text, creation date, number of likes).

Through a comparative analysis of TWIGMA with natural images and human artwork, we find that gen-AI images possess distinctive characteristics and exhibit, on average, lower variability when compared to their non-gen-AI counterparts. Additionally, we find that the similarity between a gen-AI image and human images (i) is correlated with the number of likes; and (ii) can be used to identify human images that served as inspiration for the gen-AI creations. Finally, we observe a longitudinal shift in the themes of AI-generated images on Twitter, with users increasingly sharing artistically sophisticated content such as intricate human portraits, whereas their interest in simple subjects such as natural scenes and animals has decreased. Our analyses and findings underscore the significance of TWIGMA as a unique data resource for studying AI-generated images.

Note that in accordance with the privacy and control policy of Twitter, NO raw content from Twitter is included in this dataset and users could and need to retrieve the original Twitter content used for analysis using the Twitter id. In addition, users who want to access Twitter data should consult and follow rules and regulations closely at the official Twitter developer policy at https://developer.twitter.com/en/developer-terms/policy.

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