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Alexa, International Top 100 Websites, Global, 10.12.2007
- geocommons.com
Updated Apr 29, 2008
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EmailClick to copy linkLink copiedCiteAlexa (2008). Alexa, International Top 100 Websites, Global, 10.12.2007 [Dataset]. http://geocommons.com/search.htmlDataset updatedApr 29, 2008Dataset provided byAlexa
dataDescriptionThis Dataset shows the Alexa Top 100 International Websites, and provides metrics on the volume of traffic that these sites were able to handle. The Alexa top 100 lists the 100 most visited websites in the world and measures various statistical information. I have looked up the Headquarters, either through alexa, or a Whois Lookup to get street address with i was then able to geocode. I was only able to successfully geocode 85 of the top 100 sites throughout the world. Source of Data was Alexa.com, Source URL: http://www.alexa.com/site/ds/top_sites?ts_mode=global&lang=none Data was from October 12, 2007. Alexa is updated daily so to get more up to date information visit their site directly. they don't have maps though.
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German Wake Words & Voice Commands Speech Data
- futurebeeai.com
wavUpdated Aug 1, 2022+ more versionsShareFacebookTwitterEmailClick to copy linkLink copiedCiteFutureBee AI (2022). German Wake Words & Voice Commands Speech Data [Dataset]. https://www.futurebeeai.com/dataset/wake-words-and-commands-dataset/wake-words-and-commands-german-germanywavAvailable download formatsDataset updatedAug 1, 2022Dataset provided byFutureBeeAIAuthorsFutureBee AILicensehttps://www.futurebeeai.com/policies/ai-data-license-agreementhttps://www.futurebeeai.com/policies/ai-data-license-agreement
Dataset funded byFutureBeeAIDescriptionIntroduction
The German Wake Word & Voice Command Dataset is expertly curated to support the training and development of voice-activated systems. This dataset includes a large collection of wake words and command phrases, essential for enabling seamless user interaction with voice assistants and other speech-enabled technologies. It’s designed to ensure accurate wake word detection and voice command recognition, enhancing overall system performance and user experience.
Speech Data
This dataset includes 20,000+ audio recordings of wake words and command phrases. Each participant contributed 400 recordings, captured under varied environmental conditions and speaking speeds. The data covers:
•Wake words alone•Wake words followed by command phrasesParticipant Diversity
•Speakers: 50 native German speakers from the FutureBeeAI community•Regions: Participants from various Germany provinces, ensuring broad coverage of accents and dialects•Demographics: Ages 18–70; 60% male and 40% female participantsRecording Details
•Type: Scripted wake words and command phrases•Duration: 1 to 15 seconds per clip•Format: WAV, stereo, 16-bit, with sample rates ranging from 16 kHz to 48 kHzDataset Diversity
•Wake Word Types•Automobile Wake Words: Hey Mercedes, Hey BMW, Hey Porsche, Hey Volvo, Hey Audi, Hi Genesis, Ok Ford, etc.•Voice Assistant Wake Words: Hey Siri, Ok Google, Alexa, Hey Cortana, Hi Bixby, Hey Celia, etc.•Home Appliance Wake Words: Hi LG, Ok LG, Hello Lloyd, and more•Command Types by Use Case•Automobile: Play music, check directions, voice search, provide feedback, and more•Voice Assistant: Ask general questions, make calls, control devices, shopping, manage calendars, and more•Home Appliances: Control appliances, check status, set reminders/alarms, manage shopping lists, etc.•Recording Environments•No background noise•Background traffic noise•People talking in the background•Speaking Pace•Normal speed•Fast speedThis diversity ensures robust training for real-world voice assistant applications.
Metadata
Each audio file is accompanied by detailed metadata to support advanced filtering and training needs.
•Participant Metadata: Unique ID, age, gender, region, accent, dialect•Recording Metadata: Transcript, environment, pace, device used, sample rate, bit depth, file formatUse Cases & Applications
•Voice Assistant Activation: Train models to accurately detect and trigger based on wake words•Smart Home Devices: Enable responsive voice control in smart appliances•<b style="font-weight: Get The Best Colour Lesson Plans For Kids
- kaggle.com
Updated Nov 18, 2021ShareFacebookTwitterEmailClick to copy linkLink copiedCiteKid Activities With Alexa (2021). Get The Best Colour Lesson Plans For Kids [Dataset]. https://www.kaggle.com/datasets/kidactivit/get-the-best-colour-lesson-plans-for-kidsCroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.Dataset updatedNov 18, 2021Dataset provided byKaggleAuthorsKid Activities With AlexaLicensehttps://www.usa.gov/government-works/https://www.usa.gov/government-works/
DescriptionDataset
This dataset was created by Kid Activities With Alexa
Released under U.S. Government Works
Contents
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Statistics of collected datasets.
- plos.figshare.com
xlsUpdated Jun 18, 2024ShareFacebookTwitterEmailClick to copy linkLink copiedCiteJongjin Kim; Jaeri Lee; Jeongin Yun; U. Kang (2024). Statistics of collected datasets. [Dataset]. http://doi.org/10.1371/journal.pone.0305415.t002xlsAvailable download formatsUnique identifierhttps://doi.org/10.1371/journal.pone.0305415.t002Dataset updatedJun 18, 2024Dataset provided byPLOS ONEAuthorsJongjin Kim; Jaeri Lee; Jeongin Yun; U. KangLicenseAttribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automaticallyDescriptionHow can a smart home system control a connected device to be in a desired state? Recent developments in the Internet of Things (IoT) technology enable people to control various devices with the smart home system rather than physical contact. Furthermore, smart home systems cooperate with voice assistants such as Bixby or Alexa allowing users to control their devices through voice. In this process, a user’s query clarifies the target state of the device rather than the actions to perform. Thus, the smart home system needs to plan a sequence of actions to fulfill the user’s needs. However, it is challenging to perform action planning because it needs to handle a large-scale state transition graph of a real-world device, and the complex dependence relationships between capabilities. In this work, we propose SmartAid (Smart Home Action Planning in awareness of Dependency), an action planning method for smart home systems. To represent the state transition graph, SmartAid learns models that represent the prerequisite conditions and operations of actions. Then, SmartAid generates an action plan considering the dependencies between capabilities and actions. Extensive experiments demonstrate that SmartAid successfully represents a real-world device based on a state transition log and generates an accurate action sequence for a given query.
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Tamil Wake Words & Voice Commands Speech Data
- futurebeeai.com
wavUpdated Aug 1, 2022+ more versionsShareFacebookTwitterEmailClick to copy linkLink copiedCiteFutureBee AI (2022). Tamil Wake Words & Voice Commands Speech Data [Dataset]. https://www.futurebeeai.com/dataset/wake-words-and-commands-dataset/wake-words-and-commands-tamil-indiawavAvailable download formatsDataset updatedAug 1, 2022Dataset provided byFutureBeeAIAuthorsFutureBee AILicensehttps://www.futurebeeai.com/policies/ai-data-license-agreementhttps://www.futurebeeai.com/policies/ai-data-license-agreement
Dataset funded byFutureBeeAIDescriptionIntroduction
The Tamil Wake Word & Voice Command Dataset is expertly curated to support the training and development of voice-activated systems. This dataset includes a large collection of wake words and command phrases, essential for enabling seamless user interaction with voice assistants and other speech-enabled technologies. It’s designed to ensure accurate wake word detection and voice command recognition, enhancing overall system performance and user experience.
Speech Data
This dataset includes 20,000+ audio recordings of wake words and command phrases. Each participant contributed 400 recordings, captured under varied environmental conditions and speaking speeds. The data covers:
•Wake words alone•Wake words followed by command phrasesParticipant Diversity
•Speakers: 50 native Tamil speakers from the FutureBeeAI community•Regions: Participants from various Tamil Nadu provinces, ensuring broad coverage of accents and dialects•Demographics: Ages 18–70; 60% male and 40% female participantsRecording Details
•Type: Scripted wake words and command phrases•Duration: 1 to 15 seconds per clip•Format: WAV, stereo, 16-bit, with sample rates ranging from 16 kHz to 48 kHzDataset Diversity
•Wake Word Types•Automobile Wake Words: Hey Mercedes, Hey BMW, Hey Porsche, Hey Volvo, Hey Audi, Hi Genesis, Ok Ford, etc.•Voice Assistant Wake Words: Hey Siri, Ok Google, Alexa, Hey Cortana, Hi Bixby, Hey Celia, etc.•Home Appliance Wake Words: Hi LG, Ok LG, Hello Lloyd, and more•Command Types by Use Case•Automobile: Play music, check directions, voice search, provide feedback, and more•Voice Assistant: Ask general questions, make calls, control devices, shopping, manage calendars, and more•Home Appliances: Control appliances, check status, set reminders/alarms, manage shopping lists, etc.•Recording Environments•No background noise•Background traffic noise•People talking in the background•Speaking Pace•Normal speed•Fast speedThis diversity ensures robust training for real-world voice assistant applications.
Metadata
Each audio file is accompanied by detailed metadata to support advanced filtering and training needs.
•Participant Metadata: Unique ID, age, gender, region, accent, dialect•Recording Metadata: Transcript, environment, pace, device used, sample rate, bit depth, file formatUse Cases & Applications
•Voice Assistant Activation: Train models to accurately detect and trigger based on wake words•Smart Home Devices: Enable responsive voice control in smart appliances•<b style="font-weight: 
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FacebookTwitterEmailAlexa, International Top 100 Websites, Global, 10.12.2007
data
This Dataset shows the Alexa Top 100 International Websites, and provides metrics on the volume of traffic that these sites were able to handle. The Alexa top 100 lists the 100 most visited websites in the world and measures various statistical information. I have looked up the Headquarters, either through alexa, or a Whois Lookup to get street address with i was then able to geocode. I was only able to successfully geocode 85 of the top 100 sites throughout the world. Source of Data was Alexa.com, Source URL: http://www.alexa.com/site/ds/top_sites?ts_mode=global&lang=none Data was from October 12, 2007. Alexa is updated daily so to get more up to date information visit their site directly. they don't have maps though.