A regional bakery chain wants a system that reads handwritten notes from suppliers, submitted as scanned images, and turns them into searchable digital text stored in their inventory database. Which capability of AI should the vendor propose as the core building block for this solution?
Select an answer to reveal the explanation.
Short Explanation
You need the capability that turns scanned handwriting into searchable characters, which is optical character recognition. The other ideas either analyze existing text, find objects, or process audio, so they do not solve the image-to-text problem.
Full Explanation
Optical character recognition (OCR) is purpose-built to extract text from images, including scanned documents and handwriting, and convert it into machine-readable characters that can be indexed and searched, which is exactly what the bakery needs to make supplier notes searchable in its database. Object detection is incorrect because it identifies and localizes physical objects within an image, such as boxes on a shelf, but it does not extract or interpret written characters. Sentiment analysis is incorrect because it operates on text that has already been digitized to judge emotional tone, and applying it here does nothing to solve the actual problem of getting text out of an image in the first place. Speech-to-text transcription is incorrect because it works on audio waveforms captured from spoken language, not on static images of handwriting, so there is no audio signal for it to process.