Why does speech to text (diction) suddenly become counterproductive after you own the device couple years?

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The accuracy and performance of voice dictation can be influenced by contextual factors. Context plays a significant role in speech recognition systems as they rely on patterns, language models, and statistical algorithms to interpret spoken words.

Contextual factors that can impact the accuracy of voice dictation include:

1. Words that sound similar but have different spellings and meanings can lead to errors in transcription. For example, "some" and "sum" or "thing" and "think" might be misinterpreted due to their similar pronunciation.
2. The structure and grammar of a sentence can affect how speech recognition systems interpret and transcribe spoken words. Unusual or complex sentence structures, grammatical errors, or incorrect word order can potentially lead to transcription errors.
3. Voice recognition systems may have a predefined vocabulary and be trained on specific language models. If you use domain-specific or technical terms that are not part of the system's training data, it might struggle to accurately transcribe those words.
4. Different users may have distinct speech patterns, accents, or pronunciation, which can affect the accuracy of voice dictation. Speech recognition systems typically adapt and improve over time by learning from individual user data.

It's worth noting that advancements in machine learning and artificial intelligence have enabled voice recognition systems to become more contextually aware. These systems utilize deep learning techniques and large datasets to improve accuracy by considering broader linguistic and contextual information.

However, despite advancements, speech recognition systems can still occasionally make errors, and the accuracy can vary depending on the specific implementation, device, and software version. Regular iOS updates may improve performance and address common issues.