4 datasets found
  1. Weekly time spent with music 2015-2019

    • statista.com
    Updated May 29, 2024
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    Statista (2024). Weekly time spent with music 2015-2019 [Dataset]. https://www.statista.com/statistics/828195/time-spent-music/
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    Dataset updated
    May 29, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    United States
    Description

    Data on the amount of time spent listening to music in the United States in 2019 revealed that consumers spent an average of 26.9 hours per week enjoying their favorite tunes, down from 28.3 hours per week in 2018. Weekly consumption in 2017 was even higher at 32.1 hours.

  2. s

    Spotify’s Tracks

    • searchlogistics.com
    Updated Mar 24, 2025
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    (2025). Spotify’s Tracks [Dataset]. https://www.searchlogistics.com/learn/statistics/spotify-statistics/
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    Dataset updated
    Mar 24, 2025
    License

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

    Description

    Spotify has about 80 million individual tracks on the platform.

  3. Favorite music genres in the U.S. 2018, by age

    • statista.com
    Updated May 29, 2024
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    Statista (2024). Favorite music genres in the U.S. 2018, by age [Dataset]. https://www.statista.com/statistics/253915/favorite-music-genres-in-the-us/
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    Dataset updated
    May 29, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    Jul 2018
    Area covered
    United States
    Description

    The statistic provides data on favorite music genres among consumers in the United States as of July 2018, sorted by age group. According to the source, 52 percent of respondents aged 16 to 19 years old stated that pop music was their favorite music genre, compared to 19 percent of respondents aged 65 or above. Country music in the United States – additional information

    In 2012, country music topped the list; 27.6 percent of respondents picked it among their three favorite genres. A year earlier, the result was one percent lower, which allowed classic rock to take the lead. The figures show, however, the genre’s popularity across the United States is unshakeable and it has also been spreading abroad. This could be demonstrated by the international success of (among others) Shania Twain or the second place the Dutch country duo “The Common Linnets” received in the Eurovision Song Contest in 2014, singing “Calm after the storm.”

    The genre is also widely popular among American teenagers, earning the second place and 15.3 percent of votes in a survey in August 2012. The first place and more than 18 percent of votes was awarded to pop music, rock scored 13.1 percent and landed in fourth place. Interestingly, Christian music made it to top five with nine percent of votes. The younger generation is also widely represented among country music performers with such prominent names as Taylor Swift (born in 1989), who was the highest paid musician in 2015, and Hunter Hayes (born in 1991).

    Country music is also able to attract crowds (and large sums of money) to live performances. Luke Bryan’s tour was the most successful tour in North America in 2016 based on ticket sales as almost 1.43 million tickets were sold for his shows. Fellow country singer, Garth Brooks, came second on the list, selling 1.4 million tickets for his tour in North America in 2016.

  4. T

    Data for: Ok Google, What Am I Doing? Acoustic Activity Recognition Bounded...

    • dataverse.tdl.org
    audio/vnd.wave, pdf
    Updated Oct 20, 2021
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    Rebecca Adaimi; Howard Yong; Rebecca Adaimi; Howard Yong (2021). Data for: Ok Google, What Am I Doing? Acoustic Activity Recognition Bounded by Conversational Assistant Interactions [Dataset]. http://doi.org/10.18738/T8/OCWAZW
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    audio/vnd.wave(2580538), audio/vnd.wave(2426938), audio/vnd.wave(39800), audio/vnd.wave(84412), audio/vnd.wave(80028), audio/vnd.wave(10321964), audio/vnd.wave(130540), audio/vnd.wave(9263984), audio/vnd.wave(104012), audio/vnd.wave(73012), audio/vnd.wave(134752), audio/vnd.wave(176848), audio/vnd.wave(185264), audio/vnd.wave(57822), audio/vnd.wave(160008), audio/vnd.wave(181056), audio/vnd.wave(116516), audio/vnd.wave(73622), audio/vnd.wave(7372844), audio/vnd.wave(176844), audio/vnd.wave(50598), audio/vnd.wave(105284), audio/vnd.wave(189476), audio/vnd.wave(112744), audio/vnd.wave(193684), audio/vnd.wave(102086), audio/vnd.wave(227360), audio/vnd.wave(63444), audio/vnd.wave(52772), audio/vnd.wave(160828), audio/vnd.wave(138960), audio/vnd.wave(109492), audio/vnd.wave(115412), audio/vnd.wave(81266), audio/vnd.wave(57420), audio/vnd.wave(126332), audio/vnd.wave(66642), audio/vnd.wave(61406), audio/vnd.wave(123704), audio/vnd.wave(45850), audio/vnd.wave(45766), 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audio/vnd.wave(425212), audio/vnd.wave(54820), audio/vnd.wave(96868), audio/vnd.wave(101072), audio/vnd.wave(412584), audio/vnd.wave(101706), audio/vnd.wave(293264), audio/vnd.wave(67222), audio/vnd.wave(112254), audio/vnd.wave(124486), audio/vnd.wave(92908), audio/vnd.wave(10195984), audio/vnd.wave(191244), audio/vnd.wave(88382), audio/vnd.wave(319972), audio/vnd.wave(134966), audio/vnd.wave(76926), audio/vnd.wave(311552), audio/vnd.wave(140588), audio/vnd.wave(72720), audio/vnd.wave(51436), audio/vnd.wave(99200), audio/vnd.wave(618856), audio/vnd.wave(2547770), audio/vnd.wave(125228), audio/vnd.wave(49158), audio/vnd.wave(303136), audio/vnd.wave(150564), audio/vnd.wave(54656), audio/vnd.wave(442052)Available download formats
    Dataset updated
    Oct 20, 2021
    Dataset provided by
    Texas Data Repository
    Authors
    Rebecca Adaimi; Howard Yong; Rebecca Adaimi; Howard Yong
    License

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

    Description

    An annotated dataset of audio interactions with a conversational assistant with background sounds of 19 activities. Abstract: Conversational assistants in the form of stand-alone devices such as Amazon Echo and Google Home have become popular and embraced by millions of people. By serving as a natural interface to services ranging from home automation to media players, conversational assistants help people perform many tasks with ease, such as setting timers, playing music and managing to-do lists. While these systems offer useful capabilities, they are largely passive and unaware of the human behavioral context in which they are used. In this work, we explore how off-the-shelf conversational assistants can be enhanced with acoustic-based human activity recognition by leveraging the short interval after a voice command is given to the device. Since always-on audio recording can pose privacy concerns, our method is unique in that it does not require capturing and analyzing any audio other than the speech-based interactions between people and their conversational assistants. In particular, we leverage background environmental sounds present in these short duration voice-based interactions to recognize activities of daily living. We conducted a study with 14 participants in 3 different locations in their own homes. We showed that our method can recognize 19 different activities of daily living with average precision of 84.85% and average recall of 85.67% in a leave-one-participant-out performance evaluation with 30-second audio clips bound by the voice interactions. IRB approved under ID: 2016020035-MODCR01

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Statista (2024). Weekly time spent with music 2015-2019 [Dataset]. https://www.statista.com/statistics/828195/time-spent-music/
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Weekly time spent with music 2015-2019

Explore at:
5 scholarly articles cite this dataset (View in Google Scholar)
Dataset updated
May 29, 2024
Dataset authored and provided by
Statistahttp://statista.com/
Area covered
United States
Description

Data on the amount of time spent listening to music in the United States in 2019 revealed that consumers spent an average of 26.9 hours per week enjoying their favorite tunes, down from 28.3 hours per week in 2018. Weekly consumption in 2017 was even higher at 32.1 hours.

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