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How to apply machine learning and deep learning methods to audio analysis

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While much of the writing and literature on deep learning concerns computer vision and natural language processing (NLP), audio analysis — a field that includes automatic speech recognition (ASR), digital signal processing, and music classification, tagging, and generation — is a growing subdomain of deep learning applications. Some of the most popular and widespread machine learning systems, virtual assistants Alexa, Siri and Google Home, are largely products built atop models that can extract information from audio signals.

Many of our users at Comet are working on audio related machine learning tasks such as audio classification, speech recognition and speech synthesis, so we built them tools to analyze, explore and understand audio data using Comet’s meta machine-learning platform.

Read more at Toward Data Science