Choosing the right codec and the right container helps us strike the right balance between quality and streaming ability to meet each app’s needs.
For decoding, encoding, and compression of every separate frame in a video file we use the cross-platform FFmpeg library and Video Compressor, a library based on the Telegram messenger for Android’s source code.
We record videos and apply filters to them in real time. We also add filters with extended capabilities to pre-recorded videos.
Slow Motion is recording clips at 120 FPS. We use AVFoundation for iOS to enable this feature. The diversification of Android devices makes implementation of the slow motion effect a particularly challenging task.
Stop Motion is recording very short videos consisting of 2-3 frames that create the illusion of an object moving on its own. We use MediaCodec for Android and AVFoundation for iOS to achieve slow motion.
We crop videos to match the aesthetic of the social network’s video content (Instagram, Facebook, Vimeo) for video editing apps with social sharing.
We make short videos consisting of a small number of frames which create a gif effect when looped. Animated gifs provide a fantastic way to share engaging content. We produce gif effect with the help of the FFmpeg library.
By capturing video with special effects – such as flame, snow, and rain – and also by using different filters, emoticons and text, we develop videos into rich, expressive movies.
We use the FFmpeg library to trim and blend audio tracks with video. We also use SpectrumWorx, a third-party library for audio effects for Android.
We capture voice, music, and phone calls on various devices and OSs, saving files in a variety of formats (including MP3 and WAV). We export and import audio files from or to Google Drive, Dropbox, Box and SoundCloud.
We can change voice modulation during audio recording; add background music to recordings; add special effects that alter the amplitude of voice; and change audio parameters with SpectrumWorx (using C++) to make audio processing faster.
We encode compressed audio files for transport and storage and decompress them for viewing or transcoding.
We are learning how to extract information and meaning from audio signals for analysis, classification, storage, and retrieval. The software we are working on lets users record, save, and visualize sounds as spectrograms and waveforms.
We are developing systems that analyze a person's distinctive voice. Speech recognition allows us to translate speech and authenticate and verify the identity of a speaker as part of a security process. The core technology is based on deep learning.
By using Audio Fingerprinting and matching we make it possible for mobile and wearable apps to catch sound from TV, movies, music or radio. We use ACR for creating 2nd Screen Experiences and also for “Shazam-like” video and music recognition.
For us, experimentation is a way of life. We want to do new things. To invent. Naturally, we use our inventions in our own projects, but we also share them with others. Many of our experiments and solutions are available through open source licenses, and can be found on our Github , Dribbble and Behance pages.
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