You are a machine learning specialist working for a translation service company. Your company offers several mobile applications used for translation on smartphones and tablets. As a new feature of one of your translation apps, your company offers a feature to generate handwritten notes from spoken text.
Which algorithm is the best choice for your new feature?

Answer options:

A.Long Short-Term Memory (LSTM)
B.Convolutional Neural Network
C.Multilayer Perceptron
D.Support Vector Machine

Answer: A
Option A is correct. The Long Short-Term Memory (LSTM) can work with sequences of spoken language and can be used to generate sequenced output such as handwritten text.
Option B is incorrect. Convolutional Neural Networks are primarily used to work with image data. You are working with sound data, spoken text.
Option C is incorrect. The Multilayer Perceptron algorithm is used primarily for classification predictions and regression predictions. Your problem to solve is to convert spoken text to handwritten text.
Option D is incorrect. The Support Vector Machine algorithm is primarily used for classification, regression, and anomaly detection. Your problem to solve is to convert spoken text to handwritten text.
Reference:
Please see the Machine Learning Mastery article titled When to Use MLP, CNN, and RNN Neural Networks (https://machinelearningmastery.com/when-to-use-mlp-cnn-and-rnn-neural-networks/), the SciKit Learn page titled 1.4. Support Vector Machines (https://scikit-learn.org/stable/modules/svm.html), and the Wikipedia page titled Long short-term memory (https://en.wikipedia.org/wiki/Long_short-term_memory#:~:text=Long%20short%2Dterm%20memory%20(LSTM)%20is%20an%20artificial%20recurrent,the%20field%20of%20deep%20learning.&text=LSTM%20networks%20are%20well%2Dsuited,events%20in%20a%20time%20series.)