100+ datasets found
  1. F

    Hindi Conversation Chat Dataset for Telecom Domain

    • futurebeeai.com
    wav
    Updated Aug 1, 2022
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    FutureBee AI (2022). Hindi Conversation Chat Dataset for Telecom Domain [Dataset]. https://www.futurebeeai.com/dataset/text-dataset/hindi-telecom-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/data-license-agreementhttps://www.futurebeeai.com/data-license-agreement

    Dataset funded by
    FutureBeeAI
    Description

    Introduction

    The dataset comprises over 12,000 chat conversations, each focusing on specific Telecom related topics. Each conversation provides a detailed interaction between a call center agent and a customer, capturing real-life scenarios and language nuances.

    •
    Participants Details: 200+ native Hindi participants from the FutureBeeAI community.
    •
    Word Count & Length: Chats are diverse, averaging 300 to 700 words and 50 to 150 turns across both speakers.

    Topic Diversity

    The chat dataset covers a wide range of conversations on Telecom topics, ensuring that the dataset is comprehensive and relevant for training and fine-tuning models for various Telecom use cases. It offers diversity in terms of conversation topics, chat types, and outcomes, including both inbound and outbound chats with positive, neutral, and negative outcomes.

    •Inbound Chats:
    •Phone Number Porting
    •Network Connectivity Issues
    •Billing and Payments
    •Technical Support
    •Service Activation
    •International Roaming Enquiry
    •Refunds and Billing Adjustments
    •Emergency Service Access, and many more
    •Outbound Chats:
    •Welcome Calls / Onboarding Process
    •Payment Reminders
    •Customer Surveys
    •Technical Updates
    •Service Usage Reviews
    •Network Complaint Update, and many more

    Language Variety & Nuances

    The conversations in this dataset capture the diverse language styles and expressions prevalent in Hindi Telecom interactions. This diversity ensures the dataset accurately represents the language used by Hindi speakers in Telecom contexts.

    The dataset encompasses a wide array of language elements, including:

    •
    Naming Conventions: Chats include a variety of Hindi personal and business names.
    •
    Localized Details: Real-world addresses, emails, phone numbers, and other contact information as according to different Hindi-speaking regions.
    •
    Temporal and Numeric Expressions: Dates, times, currencies, and numbers in Hindi forms, adhering to local conventions.
    •
    Idiomatic Expressions and Slang: It includes local slang, idioms, and informal phrase present in Hindi Telecom conversations.

    This linguistic authenticity ensures that the dataset equips researchers and developers with a comprehensive understanding of the intricate language patterns, cultural references, and communication styles inherent to Hindi Telecom interactions.

    Conversational Flow and Interaction Types

    The dataset includes a broad range of conversations, from simple inquiries to detailed discussions, capturing the dynamic nature of Telecom customer-agent interactions.

    •Simple Inquiries
    •Detailed Discussions
    •Transactional Interactions
    •Problem-Solving Dialogues
    •Advisory Sessions
    •Routine Checks and Follow-Ups

    Each of these conversations contains various aspects of conversation flow like:

    •Greetings
    •Authentication
    •Information gathering
    •Resolution identification
    <span

  2. F

    Hindi Conversation Chat Dataset for Healthcare Domain

    • futurebeeai.com
    wav
    Updated Aug 1, 2022
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    FutureBee AI (2022). Hindi Conversation Chat Dataset for Healthcare Domain [Dataset]. https://www.futurebeeai.com/dataset/text-dataset/hindi-healthcare-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/data-license-agreementhttps://www.futurebeeai.com/data-license-agreement

    Dataset funded by
    FutureBeeAI
    Description

    Introduction

    The dataset comprises over 12,000 chat conversations, each focusing on specific Healthcare related topics. Each conversation provides a detailed interaction between a call center agent and a customer, capturing real-life scenarios and language nuances.

    •
    Participants Details: 200+ native Hindi participants from the FutureBeeAI community.
    •
    Word Count & Length: Chats are diverse, averaging 300 to 700 words and 50 to 150 turns across both speakers.

    Topic Diversity

    The chat dataset covers a wide range of conversations on Healthcare topics, ensuring that the dataset is comprehensive and relevant for training and fine-tuning models for various Healthcare use cases. It offers diversity in terms of conversation topics, chat types, and outcomes, including both inbound and outbound chats with positive, neutral, and negative outcomes.

    •Inbound Chats:
    •Appointment Scheduling
    •New Patient Registration
    •Surgery Consultation
    •Consultation regarding Diet, and many more
    •Outbound Chats:
    •Appointment Reminder
    •Health & Wellness Subscription Programs
    •Lab Test Results
    •Health Risk Assessments
    •Preventive Care Reminders, and many more

    Language Variety & Nuances

    The conversations in this dataset capture the diverse language styles and expressions prevalent in Hindi Healthcare interactions. This diversity ensures the dataset accurately represents the language used by Hindi speakers in Healthcare contexts.

    The dataset encompasses a wide array of language elements, including:

    •
    Naming Conventions: Chats include a variety of Hindi personal and business names.
    •
    Localized Details: Real-world addresses, emails, phone numbers, and other contact information as according to different Hindi-speaking regions.
    •
    Temporal and Numeric Expressions: Dates, times, currencies, and numbers in Hindi forms, adhering to local conventions.
    •
    Idiomatic Expressions and Slang: It includes local slang, idioms, and informal phrase present in Hindi Healthcare conversations.

    This linguistic authenticity ensures that the dataset equips researchers and developers with a comprehensive understanding of the intricate language patterns, cultural references, and communication styles inherent to Hindi Healthcare interactions.

    Conversational Flow and Interaction Types

    The dataset includes a broad range of conversations, from simple inquiries to detailed discussions, capturing the dynamic nature of Healthcare customer-agent interactions.

    •Simple Inquiries
    •Detailed Discussions
    •Transactional Interactions
    •Problem-Solving Dialogues
    •Advisory Sessions
    •Routine Checks and Follow-Ups

    Each of these conversations contains various aspects of conversation flow like:

    •Greetings
    •Authentication
    •Information gathering
    •Resolution identification
    •Solution Delivery
    •Closing and Follow-ups
    •Feedback, etc

    This structured and varied conversational flow enables the creation of advanced NLP models that can effectively manage and respond to a wide range of customer service scenarios.

    Data Format and Structure

    The dataset is available in JSON, CSV, and TXT formats, with each conversation containing attributes like participant identifiers and chat messages, designed to

  3. s

    Hindi Language Datasets | Audio Data for ASR, Virtual Assistant

    • hmn.shaip.com
    • ta.shaip.com
    • +43more
    Updated Aug 30, 2024
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    Shaip (2024). Hindi Language Datasets | Audio Data for ASR, Virtual Assistant [Dataset]. https://hmn.shaip.com/offerings/speech-data-catalog/hindi-dataset/
    Explore at:
    Dataset updated
    Aug 30, 2024
    Dataset authored and provided by
    Shaip
    License

    CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
    License information was derived automatically

    Description

    Enhance your Conversational AI model with our Off-the-Shelf Hindi Language Datasets. Shaip high-quality audio datasets are a quick and effective solution for model training.

  4. F

    Hindi (India) General Conversation Speech Dataset

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

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

    Dataset funded by
    FutureBeeAI
    Description

    What’s Included

    Welcome to the Hindi Language General Conversation Speech Dataset, a comprehensive and diverse collection of voice data specifically curated to advance the development of Hindi language speech recognition models, with a particular focus on Indian accents and dialects.

    With high-quality audio recordings, detailed metadata, and accurate transcriptions, it empowers researchers and developers to enhance natural language processing, conversational AI, and Generative Voice AI algorithms. Moreover, it facilitates the creation of sophisticated voice assistants and voice bots tailored to the unique linguistic nuances found in the Hindi language spoken in India.

    Speech Data:

    This training dataset comprises 150 hours of audio recordings covering a wide range of topics and scenarios, ensuring robustness and accuracy in speech technology applications. To achieve this, we collaborated with a diverse network of 160 native Hindi speakers from different part of India. This collaborative effort guarantees a balanced representation of Indian accents, dialects, and demographics, reducing biases and promoting inclusivity.

    Each audio recording captures the essence of spontaneous, unscripted conversations between two individuals, with an average duration ranging from 15 to 60 minutes. The speech data is available in WAV format, with stereo channel files having a bit depth of 16 bits and a sample rate of 8 kHz. The recording environment is generally quiet, without background noise and echo.

    Metadata:

    In addition to the audio recordings, our dataset provides comprehensive metadata for each participant. This metadata includes the participant's age, gender, country, state, and dialect. Furthermore, additional metadata such as recording device detail, topic of recording, bit depth, and sample rate will be provided.

    The metadata serves as a valuable tool for understanding and characterizing the data, facilitating informed decision-making in the development of Hindi language speech recognition models.

    Transcription:

    This dataset provides a manual verbatim transcription of each audio file to enhance your workflow efficiency. The transcriptions are available in JSON format. The transcriptions capture speaker-wise transcription with time-coded segmentation along with non-speech labels and tags.

    Our goal is to expedite the deployment of Hindi language conversational AI and NLP models by offering ready-to-use transcriptions, ultimately saving valuable time and resources in the development process.

    Updates and Customization:

    We understand the importance of collecting data in various environments to build robust ASR models. Therefore, our voice dataset is regularly updated with new audio data captured in diverse real-world conditions.

    If you require a custom training dataset with specific environmental conditions such as in-car, busy street, restaurant, or any other scenario, we can accommodate your request. We can provide voice data with customized sample rates ranging from 8kHz to 48kHz, allowing you to fine-tune your models for different audio recording setups. Additionally, we can also customize the transcription following your specific guidelines and requirements, to further support your ASR development process.

    License:

    This audio dataset, created by FutureBeeAI, is now available for commercial use.

    Conclusion:

    Whether you are training or fine-tuning speech recognition models, advancing NLP algorithms, exploring generative voice AI, or building cutting-edge voice assistants and bots, our dataset serves as a reliable and valuable resource.

  5. F

    General domain Human-Human conversation chats in Hindi

    • futurebeeai.com
    wav
    Updated Aug 1, 2022
    + more versions
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    FutureBee AI (2022). General domain Human-Human conversation chats in Hindi [Dataset]. https://www.futurebeeai.com/dataset/text-dataset/hindi-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/data-license-agreementhttps://www.futurebeeai.com/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 Hindi 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. n

    797 Hours - Hindi(India) Spontaneous Dialogue Smartphone speech dataset

    • m.nexdata.ai
    Updated Nov 19, 2023
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    Nexdata (2023). 797 Hours - Hindi(India) Spontaneous Dialogue Smartphone speech dataset [Dataset]. https://m.nexdata.ai/datasets/speechrecog/1156
    Explore at:
    Dataset updated
    Nov 19, 2023
    Dataset provided by
    nexdata technology inc
    Authors
    Nexdata
    Variables measured
    Format, Country, Speaker, Language, Accuracy Rate, Content category, Recording device, Recording condition, Language(Region) Code, Features of annotation
    Description

    Hindi(India) Spontaneous Dialogue Smartphone speech dataset, collected from dialogues based on given topics, covering 20+ domains. Transcribed with text content, speaker's ID, gender, age and other attributes. Our dataset was collected from extensive and diversify speakers(1,002 native speakers), geographicly speaking, enhancing model performance in real and complex tasks. Quality tested by various AI companies. We strictly adhere to data protection regulations and privacy standards, ensuring the maintenance of user privacy and legal rights throughout the data collection, storage, and usage processes, our datasets are all GDPR, CCPA, PIPL complied.

  7. h

    Cross-Hindi-Hinglish-chat

    • huggingface.co
    Updated Mar 20, 2024
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    Bhabha AI (2024). Cross-Hindi-Hinglish-chat [Dataset]. https://huggingface.co/datasets/BhabhaAI/Cross-Hindi-Hinglish-chat
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Mar 20, 2024
    Dataset authored and provided by
    Bhabha AI
    Description

    Cross Hindi Hinglish Chat

    This dataset is a subset of OpenHermes where some part is converted to either Hindi or Hinglish.Note: This is in raw form. You must add "Reply in Hindi", "Reply in English" kind texts where appropriate.row_ids correspond to row id starting from 0 for OpenHermes English dataset.

  8. n

    760 Hours - Hindi(India) Spontaneous Dialogue Telephony speech dataset

    • nexdata.ai
    Updated May 31, 2023
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    Nexdata (2023). 760 Hours - Hindi(India) Spontaneous Dialogue Telephony speech dataset [Dataset]. https://www.nexdata.ai/datasets/speechrecog/1206
    Explore at:
    Dataset updated
    May 31, 2023
    Dataset provided by
    nexdata technology inc
    Authors
    Nexdata
    Variables measured
    Format, Country, Speaker, Language, Accuracy rate, Content category, Recording device, Recording condition, Language(Region) Code, Features of annotation
    Description

    Hindi(India) Spontaneous Dialogue Telephony speech dataset, collected from dialogues based on given topics, covering 20+ domains. Transcribed with text content, speaker's ID, gender, age and other attributes. Our dataset was collected from extensive and diversify speakers(1,004 native speakers), geographicly speaking, enhancing model performance in real and complex tasks. Quality tested by various AI companies. We strictly adhere to data protection regulations and privacy standards, ensuring the maintenance of user privacy and legal rights throughout the data collection, storage, and usage processes, our datasets are all GDPR, CCPA, PIPL complied.

  9. F

    Hindi Conversation Chat Dataset for Delivery & Logistics Domain

    • futurebeeai.com
    wav
    Updated Aug 1, 2022
    + more versions
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    FutureBee AI (2022). Hindi Conversation Chat Dataset for Delivery & Logistics Domain [Dataset]. https://www.futurebeeai.com/dataset/text-dataset/hindi-delivery-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/data-license-agreementhttps://www.futurebeeai.com/data-license-agreement

    Dataset funded by
    FutureBeeAI
    Description

    Introduction

    The dataset comprises over 12,000 chat conversations, each focusing on specific Delivery & Logistics related topics. Each conversation provides a detailed interaction between a call center agent and a customer, capturing real-life scenarios and language nuances.

    •
    Participants Details: 200+ native Hindi participants from the FutureBeeAI community.
    •
    Word Count & Length: Chats are diverse, averaging 300 to 700 words and 50 to 150 turns across both speakers.

    Topic Diversity

    The chat dataset covers a wide range of conversations on Delivery & Logistics topics, ensuring that the dataset is comprehensive and relevant for training and fine-tuning models for various Delivery & Logistics use cases. It offers diversity in terms of conversation topics, chat types, and outcomes, including both inbound and outbound chats with positive, neutral, and negative outcomes.

    •Inbound Chats:
    •Order Tracking
    •Delivery Complaint
    •Undeliverable Address
    •Delivery Method Selection
    •Return Process Enquiry
    •Order Modification, and many more
    •Outbound Chats:
    •Delivery Confirmation
    •Delivery Subscription
    •Incorrect Address
    •Missed Delivery Attempt
    •Delivery Feedback
    •Out-of-Stock Notification
    •Delivery Satisfaction Survey, and many more

    Language Variety & Nuances

    The conversations in this dataset capture the diverse language styles and expressions prevalent in Hindi Delivery & Logistics interactions. This diversity ensures the dataset accurately represents the language used by Hindi speakers in Delivery & Logistics contexts.

    The dataset encompasses a wide array of language elements, including:

    •
    Naming Conventions: Chats include a variety of Hindi personal and business names.
    •
    Localized Details: Real-world addresses, emails, phone numbers, and other contact information as according to different Hindi-speaking regions.
    •
    Temporal and Numeric Expressions: Dates, times, currencies, and numbers in Hindi forms, adhering to local conventions.
    •
    Idiomatic Expressions and Slang: It includes local slang, idioms, and informal phrase present in Hindi Delivery & Logistics conversations.

    This linguistic authenticity ensures that the dataset equips researchers and developers with a comprehensive understanding of the intricate language patterns, cultural references, and communication styles inherent to Hindi Delivery & Logistics interactions.

    Conversational Flow and Interaction Types

    The dataset includes a broad range of conversations, from simple inquiries to detailed discussions, capturing the dynamic nature of Delivery & Logistics customer-agent interactions.

    •Simple Inquiries
    •Detailed Discussions
    •Transactional Interactions
    •Problem-Solving Dialogues
    •Advisory Sessions
    •Routine Checks and Follow-Ups

    Each of these conversations contains various aspects of conversation flow like:

    •Greetings
    •Authentication
    •Information gathering
    •Resolution identification
    •Solution

  10. Hindi-English TED talks, Wikipedia articles, etc.

    • kaggle.com
    zip
    Updated Oct 31, 2020
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    Amay Agarwal (2020). Hindi-English TED talks, Wikipedia articles, etc. [Dataset]. https://www.kaggle.com/datasets/amayagarwal/hindienglish-ted-talks-wikipedia-articles-etc
    Explore at:
    zip(50741118 bytes)Available download formats
    Dataset updated
    Oct 31, 2020
    Authors
    Amay Agarwal
    Description

    The HindiEnCorp 0.5 dataset is a mixture of parallel Hindi and English text from various sources such as TED talks, Wikipedia articles, news, and other sources. The dataset is in .plaintext and .txt format. You can choose whichever format you find yourself most comfortable with.

    The objective here is to translate Hindi-English and vica-versa.

    Please note that this dataset is not mine.

    Citations:

    Bojar, Ondřej; Diatka, Vojtěch; Straňák, Pavel; et al., 2014, HindEnCorp 0.5, LINDAT/CLARIAH-CZ digital library at the Institute of Formal and Applied Linguistics (ÚFAL), Faculty of Mathematics and Physics, Charles University, http://hdl.handle.net/11858/00-097C-0000-0023-625F-0.

    License: Creative Commons Attribution-NonCommercial-ShareAlike 3.0 International License

  11. speech emotion recognition Hindi

    • kaggle.com
    zip
    Updated Dec 14, 2022
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    vish@lb (2022). speech emotion recognition Hindi [Dataset]. https://www.kaggle.com/datasets/vishlb/speech-emotion-recognition-hindi
    Explore at:
    zip(314911858 bytes)Available download formats
    Dataset updated
    Dec 14, 2022
    Authors
    vish@lb
    License

    Open Database License (ODbL) v1.0https://www.opendatacommons.org/licenses/odbl/1.0/
    License information was derived automatically

    Description

    Dataset

    This dataset was created by vish@lb

    Released under Database: Open Database, Contents: © Original Authors

    Contents

  12. n

    494 Hours - Hindi(India) Real-world Casual Conversation and Monologue speech...

    • nexdata.ai
    Updated Nov 11, 2023
    + more versions
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    Nexdata (2023). 494 Hours - Hindi(India) Real-world Casual Conversation and Monologue speech dataset [Dataset]. https://www.nexdata.ai/datasets/1269
    Explore at:
    Dataset updated
    Nov 11, 2023
    Dataset provided by
    nexdata technology inc
    Authors
    Nexdata
    Area covered
    World
    Variables measured
    Format, Country, Language, Accuracy Rate, Content category, Language(Region) Code, Recording environment, Features of annotation
    Description

    Hindi(India) Real-world Casual Conversation and Monologue speech dataset, covers education, interview, sports domains, mirrors real-world interactions. Transcribed with text content, speaker's ID, gender, and other attributes. Our dataset was collected from extensive and diversify speakers, geographicly speaking, enhancing model performance in real and complex tasks. Quality tested by various AI companies. We strictly adhere to data protection regulations and privacy standards, ensuring the maintenance of user privacy and legal rights throughout the data collection, storage, and usage processes, our datasets are all GDPR, CCPA, PIPL complied.

  13. h

    gooftagoo

    • huggingface.co
    Updated Mar 17, 2024
    + more versions
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    Adithya Kamath (2024). gooftagoo [Dataset]. https://huggingface.co/datasets/adi-kmt/gooftagoo
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Mar 17, 2024
    Authors
    Adithya Kamath
    License

    Apache License, v2.0https://www.apache.org/licenses/LICENSE-2.0
    License information was derived automatically

    Description

    Hindi/Hinglish Conversation Dataset

    This repository contains a dataset of conversational text in conversational hindi and hinglish(a mix of Hindi and English languages). The Conversation Dataset contains multi-turn conversations on multiple topics usually revolving around daily real-life experiences. A small amount of reasoning tasks have also been added (specifically COT style reasoning and coding) with about 1k samples from Openhermes 2.5.

      Caution
    

    This dataset… See the full description on the dataset page: https://huggingface.co/datasets/adi-kmt/gooftagoo.

  14. m

    IndicDialogue Dataset

    • data.mendeley.com
    Updated Jun 11, 2024
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    Noor Mairukh Khan Arnob (2024). IndicDialogue Dataset [Dataset]. http://doi.org/10.17632/wcb4bxbyxx.2
    Explore at:
    Dataset updated
    Jun 11, 2024
    Authors
    Noor Mairukh Khan Arnob
    License

    Attribution-NonCommercial 3.0 (CC BY-NC 3.0)https://creativecommons.org/licenses/by-nc/3.0/
    License information was derived automatically

    Description

    The IndicDialogue dataset contains raw subtitle SRT files and dialogues extracted from them. The subtitles are in 10 indic languages, namely Hindi, Bengali, Marathi, Telugu, Tamil, Urdu, Odia, Sindhi, Nepali and Assamese. This dataset provides a corpus for performing various NLP tasks in low-resource languages using SLMs(Small Language Models) and LLMs(Large Language Models).

  15. F

    Hindi Conversation Chat Dataset for Real Estate Domain

    • futurebeeai.com
    wav
    Updated Aug 1, 2022
    + more versions
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    FutureBee AI (2022). Hindi Conversation Chat Dataset for Real Estate Domain [Dataset]. https://www.futurebeeai.com/dataset/text-dataset/hindi-realestate-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/data-license-agreementhttps://www.futurebeeai.com/data-license-agreement

    Dataset funded by
    FutureBeeAI
    Description

    Introduction

    The dataset comprises over 12,000 chat conversations, each focusing on specific Real Estate related topics. Each conversation provides a detailed interaction between a call center agent and a customer, capturing real-life scenarios and language nuances.

    •
    Participants Details: 200+ native Hindi participants from the FutureBeeAI community.
    •
    Word Count & Length: Chats are diverse, averaging 300 to 700 words and 50 to 150 turns across both speakers.

    Topic Diversity

    The chat dataset covers a wide range of conversations on Real Estate topics, ensuring that the dataset is comprehensive and relevant for training and fine-tuning models for various Real Estate use cases. It offers diversity in terms of conversation topics, chat types, and outcomes, including both inbound and outbound chats with positive, neutral, and negative outcomes.

    •Inbound Chats:
    •Property Inquiry
    •Rental Property Search & Availability
    •Renovation Inquiries
    •Property Features & Amenities Inquiry
    •Investment Property Analysis & Advice
    •Property History & Ownership Details, and many more
    •Outbound Chats:
    •New Property Listing Update
    •Post Purchase Follow-ups
    •Investment Opportunities & Property Recommendations
    •Property Value Updates
    •Customer Satisfaction Surveys, and many more

    Language Variety & Nuances

    The conversations in this dataset capture the diverse language styles and expressions prevalent in Hindi Real Estate interactions. This diversity ensures the dataset accurately represents the language used by Hindi speakers in Real Estate contexts.

    The dataset encompasses a wide array of language elements, including:

    •
    Naming Conventions: Chats include a variety of Hindi personal and business names.
    •
    Localized Details: Real-world addresses, emails, phone numbers, and other contact information as according to different Hindi-speaking regions.
    •
    Temporal and Numeric Expressions: Dates, times, currencies, and numbers in Hindi forms, adhering to local conventions.
    •
    Idiomatic Expressions and Slang: It includes local slang, idioms, and informal phrase present in Hindi Real Estate conversations.

    This linguistic authenticity ensures that the dataset equips researchers and developers with a comprehensive understanding of the intricate language patterns, cultural references, and communication styles inherent to Hindi Real Estate interactions.

    Conversational Flow and Interaction Types

    The dataset includes a broad range of conversations, from simple inquiries to detailed discussions, capturing the dynamic nature of Real Estate customer-agent interactions.

    •Simple Inquiries
    •Detailed Discussions
    •Transactional Interactions
    •Problem-Solving Dialogues
    •Advisory Sessions
    •Routine Checks and Follow-Ups

    Each of these conversations contains various aspects of conversation flow like:

    •Greetings
    •Authentication
    •Information gathering
    •Resolution identification
    •Solution Delivery
    •Closing and Follow-ups
    <span

  16. Indian Languages Audio Dataset

    • kaggle.com
    Updated Nov 3, 2023
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    HARSHMAN SOLANKI (2023). Indian Languages Audio Dataset [Dataset]. https://www.kaggle.com/datasets/hmsolanki/indian-languages-audio-dataset
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Nov 3, 2023
    Dataset provided by
    Kagglehttp://kaggle.com/
    Authors
    HARSHMAN SOLANKI
    License

    Apache License, v2.0https://www.apache.org/licenses/LICENSE-2.0
    License information was derived automatically

    Area covered
    India
    Description

    Description: The "Indian Languages Audio Dataset" is a collection of audio samples featuring a diverse set of 10 Indian languages. Each audio sample in this dataset is precisely 5 seconds in duration and is provided in MP3 format. It is important to note that this dataset is a subset of a larger collection known as the "Audio Dataset with 10 Indian Languages." The source of these audio samples is regional videos freely available on YouTube, and none of the audio samples or source videos are owned by the dataset creator.

    Languages Included: 1. Bengali 2. Gujarati 3. Hindi 4. Kannada 5. Malayalam 6. Marathi 7. Punjabi 8. Tamil 9. Telugu 10. Urdu

    This dataset offers a valuable resource for researchers, linguists, and machine learning enthusiasts who are interested in studying and analyzing the phonetics, accents, and linguistic characteristics of the Indian subcontinent. It is a representative sample of the linguistic diversity present in India, encompassing a wide array of languages and dialects. Researchers and developers are encouraged to explore this dataset to build applications or conduct research related to speech recognition, language identification, and other audio processing tasks.

    Additionally, the dataset is not limited to these 10 languages and has the potential for expansion. Given the dynamic nature of language use in India, this dataset can serve as a foundation for future data collection efforts involving additional Indian languages and dialects.

    Access to the "Indian Multilingual Audio Dataset - 10 Languages" is provided with the understanding that users will comply with applicable copyright and licensing restrictions. If users plan to extend this dataset or use it for commercial purposes, it is essential to seek proper permissions and adhere to relevant copyright and licensing regulations.

    By utilizing this dataset responsibly and ethically, users can contribute to the advancement of language technology and research, ultimately benefiting language preservation, speech recognition, and cross-cultural communication.

  17. d

    HindEnCorp 0.5 - Dataset - B2FIND

    • b2find.dkrz.de
    Updated Mar 22, 2014
    + more versions
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    (2014). HindEnCorp 0.5 - Dataset - B2FIND [Dataset]. https://b2find.dkrz.de/dataset/8b3691c2-7c2b-5cc3-b9f7-12f9547eb367
    Explore at:
    Dataset updated
    Mar 22, 2014
    License

    Attribution-NonCommercial-ShareAlike 3.0 (CC BY-NC-SA 3.0)https://creativecommons.org/licenses/by-nc-sa/3.0/
    License information was derived automatically

    Description

    HindEnCorp parallel texts (sentence-aligned) come from the following sources: Tides, which contains 50K sentence pairs taken mainly from news articles. This dataset was originally col- lected for the DARPA-TIDES surprise-language con- test in 2002, later refined at IIIT Hyderabad and provided for the NLP Tools Contest at ICON 2008 (Venkatapathy, 2008). Commentaries by Daniel Pipes contain 322 articles in English written by a journalist Daniel Pipes and translated into Hindi. EMILLE. This corpus (Baker et al., 2002) consists of three components: monolingual, parallel and annotated corpora. There are fourteen monolingual sub- corpora, including both written and (for some lan- guages) spoken data for fourteen South Asian lan- guages. The EMILLE monolingual corpora contain in total 92,799,000 words (including 2,627,000 words of transcribed spoken data for Bengali, Gujarati, Hindi, Punjabi and Urdu). The parallel corpus consists of 200,000 words of text in English and its accompanying translations into Hindi and other languages. Smaller datasets as collected by Bojar et al. (2010) include the corpus used at ACL 2005 (a subcorpus of EMILLE), a corpus of named entities from Wikipedia (crawled in 2009), and Agriculture domain parallel corpus.  For the current release, we are extending the parallel corpus using these sources: Intercorp (Čermák and Rosen,2012) is a large multilingual parallel corpus of 32 languages including Hindi. The central language used for alignment is Czech. Intercorp’s core texts amount to 202 million words. These core texts are most suitable for us because their sentence alignment is manually checked and therefore very reliable. They cover predominately short sto- ries and novels. There are seven Hindi texts in Inter- corp. Unfortunately, only for three of them the English translation is available; the other four are aligned only with Czech texts. The Hindi subcorpus of Intercorp contains 118,000 words in Hindi. TED talks 3 held in various languages, primarily English, are equipped with transcripts and these are translated into 102 languages. There are 179 talks for which Hindi translation is available. The Indic multi-parallel corpus (Birch et al., 2011; Post et al., 2012) is a corpus of texts from Wikipedia translated from the respective Indian language into English by non-expert translators hired over Mechanical Turk. The quality is thus somewhat mixed in many respects starting from typesetting and punctuation over capi- talization, spelling, word choice to sentence structure. A little bit of control could be in principle obtained from the fact that every input sentence was translated 4 times. We used the 2012 release of the corpus. Launchpad.net is a software collaboration platform that hosts many open-source projects and facilitates also collaborative localization of the tools. We downloaded all revisions of all the hosted projects and extracted the localization (.po) files. Other smaller datasets. This time, we added Wikipedia entities as crawled in 2013 (including any morphological variants of the named entitity that appears on the Hindi variant of the Wikipedia page) and words, word examples and quotes from the Shabdkosh online dictionary.

  18. n

    34 Hours - Hindi(India) Children Real-world Casual Conversation and...

    • nexdata.ai
    Updated Mar 20, 2024
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    Nexdata (2024). 34 Hours - Hindi(India) Children Real-world Casual Conversation and Monologue speech dataset [Dataset]. https://www.nexdata.ai/datasets/speechrecog/1377
    Explore at:
    Dataset updated
    Mar 20, 2024
    Dataset provided by
    nexdata technology inc
    Authors
    Nexdata
    Area covered
    World
    Variables measured
    Age, Format, Country, Accuracy, Language, Content category, Language(Region) Code, Recording environment, Features of annotation
    Description

    Hindi(India) Children Real-world Casual Conversation and Monologue speech dataset, covers self-media, conversation, live, lecture, variety show and other generic domains, mirrors real-world interactions. Transcribed with text content, speaker's ID, gender, age, accent and other attributes. Our dataset was collected from extensive and diversify speakers(12 years old and younger children), geographicly speaking, enhancing model performance in real and complex tasks.Quality tested by various AI companies. We strictly adhere to data protection regulations and privacy standards, ensuring the maintenance of user privacy and legal rights throughout the data collection, storage, and usage processes, our datasets are all GDPR, CCPA, PIPL complied.

  19. F

    Hindi Conversation Chat Dataset for Travel Domain

    • futurebeeai.com
    wav
    Updated Aug 1, 2022
    + more versions
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    FutureBee AI (2022). Hindi Conversation Chat Dataset for Travel Domain [Dataset]. https://www.futurebeeai.com/dataset/text-dataset/hindi-travel-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/data-license-agreementhttps://www.futurebeeai.com/data-license-agreement

    Dataset funded by
    FutureBeeAI
    Description

    Introduction

    The dataset comprises over 12,000 chat conversations, each focusing on specific Travel related topics. Each conversation provides a detailed interaction between a call center agent and a customer, capturing real-life scenarios and language nuances.

    •
    Participants Details: 200+ native Hindi participants from the FutureBeeAI community.
    •
    Word Count & Length: Chats are diverse, averaging 300 to 700 words and 50 to 150 turns across both speakers.

    Topic Diversity

    The chat dataset covers a wide range of conversations on Travel topics, ensuring that the dataset is comprehensive and relevant for training and fine-tuning models for various Travel use cases. It offers diversity in terms of conversation topics, chat types, and outcomes, including both inbound and outbound chats with positive, neutral, and negative outcomes.

    •Inbound Calls:
    •Booking Inquiries & Assistance
    •Destination Information & Recommendations
    • Flight Delays or Cancellation Assistance
    •Assistance for Disable Passengers
    •Travel-related Health & Safety Inquiry
    •Lost or Delayed Baggage Assistance, and many more
    •Outbound Calls:
    •Promotional Offers & Package Deals
    •Customer Satisfaction Surveys
    •Booking Confirmations & Updates
    •Flight Schedule Changes & Notifications
    •Customer Feedback Collection
    •Visa Expiration Reminders, and many more

    Language Variety & Nuances

    The conversations in this dataset capture the diverse language styles and expressions prevalent in Hindi Travel interactions. This diversity ensures the dataset accurately represents the language used by Hindi speakers in Travel contexts.

    The dataset encompasses a wide array of language elements, including:

    •
    Naming Conventions: Chats include a variety of Hindi personal and business names.
    •
    Localized Details: Real-world addresses, emails, phone numbers, and other contact information as according to different Hindi-speaking regions.
    •
    Temporal and Numeric Expressions: Dates, times, currencies, and numbers in Hindi forms, adhering to local conventions.
    •
    Idiomatic Expressions and Slang: It includes local slang, idioms, and informal phrase present in Hindi Travel conversations.

    This linguistic authenticity ensures that the dataset equips researchers and developers with a comprehensive understanding of the intricate language patterns, cultural references, and communication styles inherent to Hindi Travel interactions.

    Conversational Flow and Interaction Types

    The dataset includes a broad range of conversations, from simple inquiries to detailed discussions, capturing the dynamic nature of Travel customer-agent interactions.

    •Simple Inquiries
    •Detailed Discussions
    •Transactional Interactions
    •Problem-Solving Dialogues
    •Advisory Sessions
    •Routine Checks and Follow-Ups

    Each of these conversations contains various aspects of conversation flow like:

    •Greetings
    •Authentication
    •Information gathering
    •Resolution identification
    •Solution Delivery
    <span

  20. h

    indic-instruct-data-v0.1

    • huggingface.co
    Updated Jan 25, 2024
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    AI4Bharat (2024). indic-instruct-data-v0.1 [Dataset]. https://huggingface.co/datasets/ai4bharat/indic-instruct-data-v0.1
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Jan 25, 2024
    Dataset authored and provided by
    AI4Bharat
    Description

    Indic Instruct Data v0.1

    A collection of different instruction datasets spanning English and Hindi languages. The collection consists of:

    Anudesh wikiHow Flan v2 (67k sample subset) Dolly Anthropic-HHH (5k sample subset) OpenAssistant v1 LymSys-Chat (50k sample subset)

    We translate the English subset of specific datasets using IndicTrans2 (Gala et al., 2023). The chrF++ scores of the back-translated example and the corresponding example is provided for quality assessment of… See the full description on the dataset page: https://huggingface.co/datasets/ai4bharat/indic-instruct-data-v0.1.

Share
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Click to copy link
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Close
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FutureBee AI (2022). Hindi Conversation Chat Dataset for Telecom Domain [Dataset]. https://www.futurebeeai.com/dataset/text-dataset/hindi-telecom-domain-conversation-text-dataset

Hindi Conversation Chat Dataset for Telecom Domain

Explore at:
wavAvailable download formats
Dataset updated
Aug 1, 2022
Dataset provided by
FutureBeeAI
Authors
FutureBee AI
License

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

Dataset funded by
FutureBeeAI
Description

Introduction

The dataset comprises over 12,000 chat conversations, each focusing on specific Telecom related topics. Each conversation provides a detailed interaction between a call center agent and a customer, capturing real-life scenarios and language nuances.

•
Participants Details: 200+ native Hindi participants from the FutureBeeAI community.
•
Word Count & Length: Chats are diverse, averaging 300 to 700 words and 50 to 150 turns across both speakers.

Topic Diversity

The chat dataset covers a wide range of conversations on Telecom topics, ensuring that the dataset is comprehensive and relevant for training and fine-tuning models for various Telecom use cases. It offers diversity in terms of conversation topics, chat types, and outcomes, including both inbound and outbound chats with positive, neutral, and negative outcomes.

•Inbound Chats:
•Phone Number Porting
•Network Connectivity Issues
•Billing and Payments
•Technical Support
•Service Activation
•International Roaming Enquiry
•Refunds and Billing Adjustments
•Emergency Service Access, and many more
•Outbound Chats:
•Welcome Calls / Onboarding Process
•Payment Reminders
•Customer Surveys
•Technical Updates
•Service Usage Reviews
•Network Complaint Update, and many more

Language Variety & Nuances

The conversations in this dataset capture the diverse language styles and expressions prevalent in Hindi Telecom interactions. This diversity ensures the dataset accurately represents the language used by Hindi speakers in Telecom contexts.

The dataset encompasses a wide array of language elements, including:

•
Naming Conventions: Chats include a variety of Hindi personal and business names.
•
Localized Details: Real-world addresses, emails, phone numbers, and other contact information as according to different Hindi-speaking regions.
•
Temporal and Numeric Expressions: Dates, times, currencies, and numbers in Hindi forms, adhering to local conventions.
•
Idiomatic Expressions and Slang: It includes local slang, idioms, and informal phrase present in Hindi Telecom conversations.

This linguistic authenticity ensures that the dataset equips researchers and developers with a comprehensive understanding of the intricate language patterns, cultural references, and communication styles inherent to Hindi Telecom interactions.

Conversational Flow and Interaction Types

The dataset includes a broad range of conversations, from simple inquiries to detailed discussions, capturing the dynamic nature of Telecom customer-agent interactions.

•Simple Inquiries
•Detailed Discussions
•Transactional Interactions
•Problem-Solving Dialogues
•Advisory Sessions
•Routine Checks and Follow-Ups

Each of these conversations contains various aspects of conversation flow like:

•Greetings
•Authentication
•Information gathering
•Resolution identification
<span

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