Nowadays, many devices use automatic speech recognition systems, which are based on machine learning models. But it is good to know that machine learning is not completely secure from attacks because there are Adversarial Machine Learning attacks which aims to deceive machine learning models by providing adversarial inputs. So, it is very important to understand what types of attacks are possible on these models and which defenses should be applied. For this it is necessary to analyze the various types of attacks, such as FGSM and PGD which are evasion attacks, which allow to create adversarial examples that in models without any type of defense cause a considerable decline in the performance of the model.