Engineering and Developers Blog
What's happening with engineering and developers at YouTube
Visualizing Sound Effects
Thursday, March 23, 2017
At YouTube, we understand the power of video to tell stories, move people, and leave a lasting impression. One part of storytelling that many people take for granted is sound, yet sound adds color to the world around us. Just imagine not being able to hear music, the joy of a baby laughing, or the roar of a crowd. But this is often a reality for the
360 million people
around the world who are deaf and hard of hearing. Over the last decade, we have been working to change that.
The first step came over ten years ago with the launch of
captions
. And in an effort to scale this technology,
automated captions
came a few years later. The success of that effort has been astounding, and a few weeks ago we
announced
that the number of videos with automatic captions now exceeds 1 billion. Moreover, people watch videos with automatic captions more than 15 million times per day. And we have made meaningful improvements to quality, resulting in a 50 percent leap in accuracy for automatic captions in English, which is getting us closer and closer to human transcription error rates.
But there is more to sound and the enjoyment of a video than words. In a joint effort between YouTube, Sound Understanding, and Accessibility teams, we embarked on the task of developing the first ever automatic sound effect captioning system for YouTube. This means finding a way to identify and label all those other sounds in the video without manual input.
We started this project by taking on a wide variety of challenges, such as how to best design the sound effect recognition system and what sounds to prioritize. At the heart of the work was utilizing thousands of hours of videos to train a deep neural network model to achieve high quality recognition results. There are more details in a companion post
here
.
As a result, we can now automatically detect the existence of these sound effects in a video and transcribe it to appropriate classes or sound labels. With so many sounds to choose from, we started with [APPLAUSE], [MUSIC] and [LAUGHTER], since these were among the most frequent manually captioned sounds, and they can add meaningful context for viewers who are deaf and hard of hearing.
So what does this actually look like when you are watching a YouTube video? The sound effect is merged with the automatic speech recognition track and shown as part of standard automatic captions.
Click the CC button to see the sound effect captioning system in action
We are still in the early stages of this work, and we are aware that these captions are fairly simplistic. However, the infrastructural backend to this system will allow us to expand and easily apply this framework to other sound classes. Future challenges might include adding other common sound classes like ringing, barking and knocking, which present particular problems -- for example, with ringing we need to be able to decipher if this is an alarm clock, a door or a phone as described
here
.
Since the addition of sound effect captions presented a number of unique challenges on both the machine learning end as well as the user experience, we continue to work to better understand the effect of the captioning system on the viewing experience, how viewers use sound effect information, and how useful it is to them. From our initial user studies, two-thirds of participants said these sound effect captions really enhance the overall experience, especially when they added crucial “invisible” sound information that people cannot tell from the visual cues. Overall, users reported that their experience wouldn't be impacted by the system making occasional mistakes as long as it was able to provide good information more often than not.
We are excited to support automatic sound effect captioning on YouTube, and we hope this system helps us make information useful and accessible for everyone.
Noah Wang, software engineer, recently watched "
The Expert (Short Comedy Sketch)
."
YouTube @ Google I/O: All About Captioning
Friday, June 3, 2011
Google I/O 2011
may be over, but we’re continuing our series of blog posts recapping the great developer material covered at the event. We previously covered our talk on the
iframe Player API
, and the next presentation we’re highlighting is “
The YouTube Caption API, Speech Recognition, and WebVTT captions for HTML5
”.
The session features Jeff Posnick from the YouTube Developer Relations team, Naomi Black from the Accessibility Engineering team, and Cynthia Boedihardjo, a Live Stream Program Manager. As the session’s title suggests, a number of different topics were covered, with video accessibility and captions the common theme throughout.
The material covering the
YouTube Captions API
, including a
sample application
that demonstrates using the API from Python, will be of particular interest to the YouTube API developer community. The talk also includes some early WebKit demos of WebVTT implementations for the <track> element in HTML5 as well as more information and stats about the
Live Caption gadget
launched at Google I/O. The gadget provides captions alongside streaming video.
The full video of the session is embedded below, and
the slides
from the talk are available as well.
Cheers,
—Jeff Posnick, YouTube API Team
YouTube Captions Uploader Web App
Thursday, January 27, 2011
Captions can greatly enhance the experience of viewing a YouTube video, and the YouTube API has offered developers ways to
upload
and
retrieve
caption data in authorized requests for a while now. However, the various YouTube API
client libraries
don’t natively support interacting with captions at this time, and writing your own code for uploading or retrieving captions can be challenging.
With that in mind, we're happy to announce the
YouTube Captions Uploader
open source project on Google Code, which provides real-world code for uploading captions to YouTube. The code is written for the Java App Engine environment, and it uses some nifty new App Engine features like the
Channel API
, the
Blobstore Service
, and
Task Queues
. And even if you're not an App Engine developer, we hope that the
code
that interacts with the YouTube API's captions service will provide a good starting point for writing your own code.
In addition to open sourcing the code for this project, we’re also running the code itself on a public App Engine instance,
http://yt-captions-uploader.appspot.com/
. So, even if you're not a developer, you can still use the application to upload captions for videos in your YouTube account.
Please share your comments or feedback via the project’s
issue tracker
. We hope that you find it useful both as a standalone web application and as a starting point for writing your own code!
Cheers,
—Jeff Posnick, YouTube API Team
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