United States call centers generate more than a billion hours of audio recordings every year and less than 25% of the audio is made searchable or analyzed.
Launching out of Y Combinator’s Winter 2016 class, DeepGram uses deep learning and GPUs hosted in the Amazon Web Services cloud to quickly index audio and make it searchable.
The free demo on the DeepGram site allows you to upload or provide a URL for an audio file, enter a keyword or phrase, and quickly analyze the audio to highlight precisely all the places your keyword is mentioned.
Below is the result – the red mark indicates where ‘NVIDIA’ is mentioned in a recent Share Your Science interview with Jeroen Tromp of Princeton.
The Y Combinator blog post outlines how speech search is motivated by market factors. There has been a structural change in phone support from on-site employees to a distributed, international workforce which makes quality assurance more challenging. Businesses are also focusing more on data and analytics, and they want actionable insights from their information-rich audio datasets.
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Related resources
- GTC session: 3D Audio: Spatial Sound Classification, Segmentation, and Localization using Deep Learning (Spring 2023)
- GTC session: Speech AI Demystified (Spring 2023)
- GTC session: Audio Research at NVIDIA's Applied Deep Learning Research (Spring 2023)
- Webinar: Inception Workshop 101 - Getting Started with Conversational AI
- Webinar: Inception Workshop 101 - Getting Started with Vision AI
- Webinar: Inception Workshop 101 - Getting Started with Data Science
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