The text discusses six challenges in training a Dutch automatic speech recognition (ASR) model due to the language's diverse dialects, data, and dictionaries. These include inflection, compound words, different dialects, vocabulary size issues, pronunciation variations, and potential biases introduced by standardizing data. The article emphasizes that these challenges make it difficult for ASR models to accurately transcribe speech in various varieties of Dutch.