It is vital for Apple to refine its OCR models to correctly distinguish between Khmer and Thai scripts. Incorrectly labeling Khmer text as Thai is more than a technical bug; it is a culturally insensitive error that impacts national identity, especially given the current geopolitical climate between Cambodia and Thailand. Implementing a more robust language-detection threshold would prevent these harmful misidentifications.
There is a significant logic flaw in the VNRecognizeTextRequest language detection when processing Khmer script. When the property automaticallyDetectsLanguage is set to true, the Vision framework frequently misidentifies Khmer characters as Thai.
While both scripts share historical roots, they are distinct languages with different alphabets. Currently, the model’s confidence threshold for distinguishing between these two scripts is too low, leading to incorrect OCR output in both developer-facing APIs and Apple’s native ecosystem (Preview, Live Text, and Photos).
import SwiftUI
import Vision
class TextExtractor {
func extractText(from data: Data, completion: @escaping (String) -> Void) {
let request = VNRecognizeTextRequest { (request, error) in
guard let observations = request.results as? [VNRecognizedTextObservation] else {
completion("No text found.")
return
}
let recognizedStrings = observations.compactMap { observation in
let str = observation.topCandidates(1).first?.string
return "{text: \(str!), confidence: \(observation.confidence)}"
}
completion(recognizedStrings.joined(separator: "\n"))
}
request.automaticallyDetectsLanguage = true // <-- This is the issue.
request.recognitionLevel = .accurate
let handler = VNImageRequestHandler(data: data, options: [:])
DispatchQueue.global(qos: .background).async {
do {
try handler.perform([request])
} catch {
completion("Failed to perform OCR: \(error.localizedDescription)")
}
}
}
}
Recognizing Khmer
Confidence Score is low for Khmer text. (The output is in Thai language with low confidence score)
Recognizing English
Confidence Score is high expected.
Recognizing Thai
Confidence Score is high as expected
Issues on Preview, Photos
Khmer text
Copied text
Kouk Pring Chroum Temple [19121 รอาสายสุกตีนานยารรีสใหิสรราภูชิตีนนสุฐตีย์ [รุก
เผือชิษาธอยกัตธ์ตายตราพาษชาณา ถวเชยาใบสราเบรถทีมูสินตราพาษชาณา ทีมูโษา เช็ก
อาษเชิษฐอารายสุกบดตพรธุรฯ ตากร"สุก"ผาตากรธกรธุกเยากสเผาพศฐตาสาย รัอรณาษ"ตีพย"
สเผาพกรกฐาภูชิสาเครๆผู:สุกรตีพาสเผาพสรอสายใผิตรรารตีพสๆ เดียอลายสุกตีน
ธาราชรติ ธิพรหณาะพูชุบละเาหLunet De Lajonquiere ผารูกรสาราพารผรผาสิตภพ ตารสิทูก ธิพิ
คุณที่นสายเระพบพเคเผาหนารเกะทรนภาษเราภุพเสารเราษทีเลิกสญาเราหรุฬารชสเกาก เรากุม
สงสอบานตรเราะากกต่ายภากายระตารุกเตียน
Recommended Solutions
1. Set a Threshold
Filter out the detected result where the threshold is less than or equal to 0.5, so that it would not output low quality text which can lead to the issue.
For example,
let recognizedStrings = observations.compactMap { observation in
if observation.confidence <= 0.5 {
return nil
}
let str = observation.topCandidates(1).first?.string
return "{text: \(str!), confidence: \(observation.confidence)}"
}
2. Add Khmer Language Support
This issue would never happen if the model has the capability to detect and recognize image with Khmer language.
Doc2Text GitHub: https://github.com/seanghay/Doc2Text-Swift
