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  3. MusicLM


Audio Editing

Google Research is a project that hosts various research activities and publications by Google researchers and engineers. It covers a wide range of topics, such as computer vision, natural language processing, machine learning, quantum computing, security, and more. Google Research also releases open-source code, datasets, and tools to support the research community and foster collaboration.

One of the sub-projects of Google Research is MusicLM, which is a model that can generate high-fidelity music from text descriptions. For example, given a text like "a calming violin melody backed by a distorted guitar riff", MusicLM can produce a realistic audio clip that matches the style and mood of the text. MusicLM uses a hierarchical sequence-to-sequence model that can generate music at 24 kHz and remain consistent over several minutes. MusicLM can also be conditioned on both text and a melody, such as a whistled or hummed tune, and transform it according to the text caption.

To support the development of MusicLM, Google Research released MusicCaps, a dataset composed of 5.5k music-text pairs, with rich text descriptions provided by human experts. MusicCaps can be used to train and evaluate models for music generation from text, as well as for other tasks such as music captioning, retrieval, and classification.

  • It showcases a variety of research projects from Google on topics such as machine learning, natural language processing, computer vision, robotics, and more.
  • It provides links to papers, datasets, code, and demos for each project, making it easy to access and reproduce the research results.
  • It encourages open collaboration and feedback from the research community by hosting the code on GitHub and allowing issues and pull requests.

  • It may not cover all the research areas or projects that Google is working on, so it may not reflect the full scope or diversity of Google's research.
  • It may not be updated frequently or consistently, so some projects may be outdated or incomplete.
  • It may not provide enough details or explanations for some projects, especially for those that are complex or novel, making it hard to understand or apply them.

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