LLet’s start with the questions that seem to be on everyone’s mind. If you don’t see the answers you seek, please fill out the “Submit a help request” form below. For non-technical questions, please Contact Us.
One call is required to get an authentication token, which is valid for a time interval. After obtaining the authentication token, only one call is required to enhance audio.
Yes! Please contact us.
We apply a pre-processing algorithm to regularize the received signal. Next it gets passed through a neural network (NN) subsystem to isolate and reconstruct the speech signal. Finally, we take the NN output to derive a statistical model of the speech that we use to suppress any noise in the received audio stream. This yields natural speech with minimal reverberation, mixed with a controlled level of the background noise to preserve the naturalness of the audio file. Also, we preserve the speech signal at the same level it was in the received file, to give you full control over any level adjustment that you might want to apply. The average volume of the speech signal is scaled to 0.9x the original value to avoid saturation. Since noise is removed from the stream, the perceived volume can be meaningfully lower for signals with a lot of noise, and you might wish to normalize the volume to compensate.
BabbleLabs applies deep neural networks — sophisticated mathematical models, trained to perform a complex task — to mimic the capabilities of specific human cognition skills. Distinguishing speech from background sounds is remarkably difficult, because those interfering sounds often are occurring at the same time, in the same frequency ranges, and are often fluctuating as rapidly as the speech.
All traditional methods try to identify statistical characteristics of speech vs. noise, and use these statistics to suppress the noise while preserving the speech. This approach can work for stationary (non-varying) noise, but it cannot handle transient noise well. Just as humans learn to extract the thread of speech from background sounds, including interfering speech, neural networks are trained on extensive sequences of real human speech and real noise. These algorithms learn to isolate and regenerate the human speech without the noise by using a longer context of past speech.
BabbleLabs has gathered a unique database of noisy speech and applies hundreds of thousands of hours of natural speech in training its production networks, enabling accurate separation of speech from noise — across different languages, speaking styles, vocabulary, noise types and noise intensities.
Yes! Our algorithms work on each channel individually. You send us the number of output channels for stereo inputs, and we will either process each channel individually or convert the data to mono. Processing each channel will provide a richer experience, but you will be charged separately for each channel. Channels converted to mono will be charged the rate for a single channel. Streams with more than two channels will always be converted to at most two channels.
Our algorithms work natively on 16,000 Hz. Other sample rates will be down- or up- sampled to 16,000 Hz.
Yes. You can either submit:
We should be able to handle any size file, but we are expecting users to upload movie-length or less (i.e., under 2 hours). Typical uses include 30-60 minute interviews or presentations, short documentaries, and clips designed for social media sharing or YouTube.
Listen to it! Then, send us your feedback, we would love to hear what you have to say. Soon, BabbleLabs will also be sharing with you metrics and comparative analysis of the input stream and the output stream, to give you a better idea of how we did, objectively and subjectively.
Our users have been busy conquering unwanted noise. Check out Gabby’s Lab to see what Clear Cloud can do for you in real-world environments and use cases.
Both! The Apple version is supported on iOS 11 and higher, and is a universal app. The Android app is supported on OS 5 and higher. We welcome your feedback; please contact us.
You don’t have to register to get started — you can use up to $5 worth of processing time (250 audio, 125 video minutes equivalent) before we will require you to register.
You can shoot audio/video and enhance it immediately through the app. You can also enhance existing files stored on your phone. On an iPhone, you can enhance any video stored in your Photos app. On Android, you can enhance video files stored in various places on your phone, including Camera, Google Gallery, and Instagram; the enhanced files will be stored in the app and album you uploaded from. For both iOS and Android, you will find enhanced files in the Clear Cloud folder. On iPhones, this folder lives in the Photos app. On Android phones, it lives in the Gallery app.
For the iPhone app, once you have used up the free processing minutes provided (250 minutes of audio or 125 minutes of video), you can add $4.99 to your app account to continue enhancing your audio and video files. You can also register on our site to be directly billed by BabbleLabs for processing time. For Android users, once you add your billing information on our web site, there is no need to do anything else. After you have signed in to our site, you can find the billing page in the menu under your user name.
For iPhone users, you can export audio from other apps into Clear Cloud. Enhanced audio files are stored in an audio album managed by the Clear Cloud App.
For Android users, you can only create and enhance audio-only files within the Clear Cloud App. The enhanced audio files are accessible in the Audio portion of the Clear Cloud App, where they can be easily located, named and managed.
On your iPhone, make sure that the Ring/Silent switch is in the “on” position and the volume is turned up. Check to see if anything is covering the microphone/speaker area on the bottom of the iPhone.
Both versions of the app (iOS and Android) keep your audio and video files completely private. Even though the app itself gets access to your existing audio and video clips, it never stores anything in the cloud or shares anything with BabbleLabs.
In the app, tap the “hamburger menu” and select Support. Enter your question. We’ll respond to you via the email address you provide. If you prefer, you can submit a help request using the form below.
Yes. Once you have signed in on our website, go to the user name drop down menu, choose "Billing" and set your monthly billing limit. (BabbleLabs has set a default limit set of $2000 per month.)
Yes. We will charge for each audio or video stream after the entire stream has been enhanced. This means that if you are near your monthly limit and upload a stream that exceeds the time remaining, you will be charged accordingly for the overage (standard per minute pricing applies). For example, if you have 5 minutes remaining until you reach your limit, then you upload a 25 minute video file, you will be charged 80 cents for the 20 minutes above your limit (20 minutes x 4 cents/per minute for video processing).
Once you are registered and signed in to the BabbleLabs web site, you can click “Usage Statistics” in the upper right corner of the home page to see what portion of your monthly limit has been used.
If you can figure out a way to pay that results in US dollars, sure!
All data is transmitted to and from our servers encrypted using https. We do not store your audio/video material.
No! BabbleLabs wants to enhance, improve and personalize your audio and video streams, not use your streaming data to market to you.
Send contact us with your request.
We know a lot about embedding Clear Cloud to give your device a differentiated video or audio result! We’d love to hear about your project — please contact us.
Yes! We’re looking for partners in speech processing and deep learning (cloud or embedded) as well as experts in speech metrics and researchers from university programs in related fields.
We are working toward establishing an active customer community. Likewise, we want to build and foster a community of enthusiastic experts, developers, end-users, and innovators. Interested? Send us with your contact info and the area/manner in which you would like to partner.
We announced a successful round of funding in January 2018. This Series Seed investment of $4 million led by Cognite Ventures is being used for initial development and productization. We are always interested in hearing from our colleagues; we know the technology space we’re in is exceptionally active, with a growing focus on voice interfaces and deep learning.
Yes, we are looking for interns! We don’t yet have a formal internship program. Take a look at our Careers information. If you believe you have directly relevant skills — and you have a passion for speech enhancement, speech-centric technology, and deep learning — contact us.
We welcome your help in spreading the word about the exciting developments here at BabbleLabs. Please send an inquiry with a brief abstract to us from our contact page.