First, it assumes that the pipeline will accept a large binary file as input. Klio currently enables a few key steps to create the desired pipeline.
Now that Klio has been released as open source, anyone can use the framework to build their own scalable and efficient media processing workflows. Klio simplifies and standardizes pipeline creation for these tasks, increasing efficiency and letting users focus on their business objectives rather than maintaining the processing infrastructure. There are a multitude of possible use cases for audio alone, from standardizing common audio-processing tasks with ffmpeg or librosa to running custom machine learning models. Spotify saw an opportunity to produce a flexible, managed process that would support a variety of audio processing use cases over time-efficiently and at scale-and got to work.Īt a high level, Klio allows a user to provide a media file as input, perform the necessary processing, and output intelligent features and data. Spotify originally created Klio after realizing that ML and audio researchers across the company were performing similar audio processing tasks, but were struggling to deploy and maintain them. In order to productionize audio processing, Spotify created Klio-a framework built on top of Apache Beam for Python that helps researchers and engineers alike run large-scale data pipelines for processing audio and other media files (such as video and images). This scale and complexity-plus, the difficulty of handling large binary files to begin with-can hinder collaboration and efficiency, bringing product development to a grinding halt. Then, factor in that hundreds of product teams are processing these tracks at the same time, all around the world, and for different use cases. But Spotify’s music library is over 60 million songs, growing by 40,000 tracks a day, not including the rapidly expanding podcast catalog.
This might be done to develop a new feature, to help inform playlists and recommendations, or for pure research.ĭoing this kind of processing on a single audio file is one thing. On any given day, music streaming service Spotify might process an audio file a hundred different ways-identifying a track’s rhythm and tempo, timestamping beats, and measuring loudness-as well as more sophisticated processing, such as detecting languages and separating vocals from instruments.
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