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Cambodia Language bugs
Dear Apple Support Team, I am writing to report a long-standing issue affecting Khmer (Cambodia) text recognition in Live Text and the Vision Framework OCR. Based on my testing, this issue has persisted for more than two years—from iOS 17 through iOS 27 Beta 3—and is also reproducible on iPadOS and macOS. I would appreciate clarification on the following points: Is Apple aware of an issue where Live Text incorrectly recognizes Khmer script as Thai script, causing copied text to output as Thai characters instead of Khmer? Has this issue been officially logged as a bug within the Vision Framework or Live Text teams? Since this behavior has remained reproducible since iOS 17, why has it not yet been resolved? Is the problem caused by automatic language detection, the OCR recognition model, the Vision Framework, or another component of Apple's AI pipeline? Does Apple currently have a dedicated OCR and language recognition model for the Khmer script, or is Khmer being inferred through another language model? Is there an estimated timeline for improving Khmer OCR and preventing Khmer text from being misidentified as Thai? Can Apple confirm whether this issue affects all products using the Vision Framework, including Live Text, Photos Preview, Screenshot OCR, and APIs provided to third-party developers? How can Apple work with the Khmer technology community to improve OCR accuracy and language support for Cambodia? This issue is more than a simple OCR bug. When Khmer text is automatically converted into Thai characters, users lose access to the original text, developers receive incorrect OCR output, and it negatively impacts the digital representation of the Khmer language. For reference, I have documented the issue in detail here: https://app.notion.com/p/Inaccurate-OCR-Language-Inference-Khmer-Script-Misidentified-as-Thai-in-Vision-Framework-2d8a24f4ee6680fcbc49d989f8bb606f I hope Apple will investigate this issue and prioritize improving Khmer language support across the Vision Framework and Live Text. Thank you, Vattanak Khun
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Cambodia Language bugs
Dear Apple Support Team, I am writing to report a long-standing issue affecting Khmer (Cambodia) text recognition in Live Text and the Vision Framework OCR. Based on my testing, this issue has persisted for more than two years—from iOS 17 through iOS 27 Beta 3—and is also reproducible on iPadOS and macOS. I would appreciate clarification on the following points: Is Apple aware of an issue where Live Text incorrectly recognizes Khmer script as Thai script, causing copied text to output as Thai characters instead of Khmer? Has this issue been officially logged as a bug within the Vision Framework or Live Text teams? Since this behavior has remained reproducible since iOS 17, why has it not yet been resolved? Is the problem caused by automatic language detection, the OCR recognition model, the Vision Framework, or another component of Apple's AI pipeline? Does Apple currently have a dedicated OCR and language recognition model for the Khmer script, or is Khmer being inferred through another language model? Is there an estimated timeline for improving Khmer OCR and preventing Khmer text from being misidentified as Thai? Can Apple confirm whether this issue affects all products using the Vision Framework, including Live Text, Photos Preview, Screenshot OCR, and APIs provided to third-party developers? How can Apple work with the Khmer technology community to improve OCR accuracy and language support for Cambodia? This issue is more than a simple OCR bug. When Khmer text is automatically converted into Thai characters, users lose access to the original text, developers receive incorrect OCR output, and it negatively impacts the digital representation of the Khmer language. For reference, I have documented the issue in detail here: https://app.notion.com/p/Inaccurate-OCR-Language-Inference-Khmer-Script-Misidentified-as-Thai-in-Vision-Framework-2d8a24f4ee6680fcbc49d989f8bb606f I hope Apple will investigate this issue and prioritize improving Khmer language support across the Vision Framework and Live Text. Thank you, Vattanak Khun
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