Blog
The latest from Google Research
Discovering Talented Musicians with Acoustic Analysis
Wednesday, November 2, 2011
Posted by Charles DuHadway, YouTube Slam Team, Google Research
In an
earlier post
we talked about the technology behind Instant Mix for
Music Beta by Google
. Instant Mix uses machine hearing to characterize music attributes such as its timbre, mood and tempo. Today we would like to talk about acoustic and visual analysis -- this time on YouTube. A fundamental part of YouTube's mission is to allow anyone anywhere to showcase their talents -- occasionally leading to
life-changing success
-- but many talented performers are never discovered. Part of the problem is the sheer volume of videos: forty eight hours of video are uploaded to YouTube every minute (that’s eight years of content every day). We wondered if we could use acoustic analysis and machine learning to pore over these videos and automatically identify talented musicians.
First we analyzed audio and visual features of videos being uploaded. We wanted to find “singing at home” videos -- often correlated with features such as ambient indoor lighting, head-and-shoulders view of a person singing in front of a fixed camera, few instruments and often a single dominant voice. Here’s a sample set of videos we found.
Then we estimated the quality of singing in each video. Our approach is based on acoustic analysis similar to that used by Instant Mix, coupled with a small set of singing quality annotations from human raters. Given these data we used machine learning to build a ranker that predicts if an average listener would like a performance.
While machines are useful for weeding through thousands of not-so-great videos to find potential stars, we know they alone can't pick the next great star. So we turn to YouTube users to help us identify the real hidden gems by playing a voting game called
YouTube Slam
. We're putting an equal amount of effort into the game itself -- how do people vote? What makes it fun? How do we know when we have a true hit? We're looking forward to your feedback to help us refine this process:
give it a try
*. You can also check out singer and voter
leaderboards
. Toggle “All time” to “Last week” to find emerging talent in fresh videos or all-time favorites.
Our “Music Slam” has only been running for a few weeks and we have already found some very talented musicians. Many of the videos have less than 100 views when we find them.
And while we're excited about what we've done with music, there's as much undiscovered potential in almost any subject you can think of. Try our other slams:
cute
,
bizarre
,
comedy
, and
dance
*. Enjoy!
Related work by Google Researchers:
“
Video2Text: Learning to Annotate Video Content
”,
Hrishikesh Aradhye
,
George Toderici
,
Jay Yagnik
, ICDM Workshop on Internet Multimedia Mining, 2009.
* Music and dance slams are currently available only in the US.
Labels
accessibility
ACL
ACM
Acoustic Modeling
Adaptive Data Analysis
ads
adsense
adwords
Africa
AI
AI for Social Good
Algorithms
Android
Android Wear
API
App Engine
App Inventor
April Fools
Art
Audio
Augmented Reality
Australia
Automatic Speech Recognition
AutoML
Awards
BigQuery
Cantonese
Chemistry
China
Chrome
Cloud Computing
Collaboration
Compression
Computational Imaging
Computational Photography
Computer Science
Computer Vision
conference
conferences
Conservation
correlate
Course Builder
crowd-sourcing
CVPR
Data Center
Data Discovery
data science
datasets
Deep Learning
DeepDream
DeepMind
distributed systems
Diversity
Earth Engine
economics
Education
Electronic Commerce and Algorithms
electronics
EMEA
EMNLP
Encryption
entities
Entity Salience
Environment
Europe
Exacycle
Expander
Faculty Institute
Faculty Summit
Flu Trends
Fusion Tables
gamification
Gboard
Gmail
Google Accelerated Science
Google Books
Google Brain
Google Cloud Platform
Google Docs
Google Drive
Google Genomics
Google Maps
Google Photos
Google Play Apps
Google Science Fair
Google Sheets
Google Translate
Google Trips
Google Voice Search
Google+
Government
grants
Graph
Graph Mining
Hardware
HCI
Health
High Dynamic Range Imaging
ICCV
ICLR
ICML
ICSE
Image Annotation
Image Classification
Image Processing
Inbox
India
Information Retrieval
internationalization
Internet of Things
Interspeech
IPython
Journalism
jsm
jsm2011
K-12
Kaggle
KDD
Keyboard Input
Klingon
Korean
Labs
Linear Optimization
localization
Low-Light Photography
Machine Hearing
Machine Intelligence
Machine Learning
Machine Perception
Machine Translation
Magenta
MapReduce
market algorithms
Market Research
materials science
Mixed Reality
ML
ML Fairness
MOOC
Moore's Law
Multimodal Learning
NAACL
Natural Language Processing
Natural Language Understanding
Network Management
Networks
Neural Networks
NeurIPS
Nexus
Ngram
NIPS
NLP
On-device Learning
open source
operating systems
Optical Character Recognition
optimization
osdi
osdi10
patents
Peer Review
ph.d. fellowship
PhD Fellowship
PhotoScan
Physics
PiLab
Pixel
Policy
Professional Development
Proposals
Public Data Explorer
publication
Publications
Quantum AI
Quantum Computing
Recommender Systems
Reinforcement Learning
renewable energy
Research
Research Awards
resource optimization
Responsible AI
Robotics
schema.org
Search
search ads
Security and Privacy
Self-Supervised Learning
Semantic Models
Semi-supervised Learning
SIGCOMM
SIGMOD
Site Reliability Engineering
Social Networks
Software
Sound Search
Speech
Speech Recognition
statistics
Structured Data
Style Transfer
Supervised Learning
Systems
TensorBoard
TensorFlow
TPU
Translate
trends
TTS
TV
UI
University Relations
UNIX
Unsupervised Learning
User Experience
video
Video Analysis
Virtual Reality
Vision Research
Visiting Faculty
Visualization
VLDB
Voice Search
Wiki
wikipedia
WWW
Year in Review
YouTube
Archive
2021
Oct
Sep
Aug
Jul
Jun
May
Apr
Mar
Feb
Jan
2020
Dec
Nov
Oct
Sep
Aug
Jul
Jun
May
Apr
Mar
Feb
Jan
2019
Dec
Nov
Oct
Sep
Aug
Jul
Jun
May
Apr
Mar
Feb
Jan
2018
Dec
Nov
Oct
Sep
Aug
Jul
Jun
May
Apr
Mar
Feb
Jan
2017
Dec
Nov
Oct
Sep
Aug
Jul
Jun
May
Apr
Mar
Feb
Jan
2016
Dec
Nov
Oct
Sep
Aug
Jul
Jun
May
Apr
Mar
Feb
Jan
2015
Dec
Nov
Oct
Sep
Aug
Jul
Jun
May
Apr
Mar
Feb
Jan
2014
Dec
Nov
Oct
Sep
Aug
Jul
Jun
May
Apr
Mar
Feb
Jan
2013
Dec
Nov
Oct
Sep
Aug
Jul
Jun
May
Apr
Mar
Feb
Jan
2012
Dec
Oct
Sep
Aug
Jul
Jun
May
Apr
Mar
Feb
Jan
2011
Dec
Nov
Sep
Aug
Jul
Jun
May
Apr
Mar
Feb
Jan
2010
Dec
Nov
Oct
Sep
Aug
Jul
Jun
May
Apr
Mar
Feb
Jan
2009
Dec
Nov
Aug
Jul
Jun
May
Apr
Mar
Feb
Jan
2008
Dec
Nov
Oct
Sep
Jul
May
Apr
Mar
Feb
2007
Oct
Sep
Aug
Jul
Jun
Feb
2006
Dec
Nov
Sep
Aug
Jul
Jun
Apr
Mar
Feb
Feed
Follow @googleai
Give us feedback in our
Product Forums
.
