To which of these tasks would you apply a many-to-one RNN architecture?Question 7Answera.   Both sentiment classification and gender recognition from speechb.Gender recognition from speech (input an audio clip and output a label indicating the speaker’s gender)c.   Speech recognition (input an audio clip and output a transcript)d. Sentiment classification (input a piece of text and output a 0/1 to denote positive or negative sentiment)

Which RNN network structure would best fit a text analysis task, where the occurences of references to a specific kind of event is searched for?

In NLP, what does RNNs help to predict?Next song noteNext imageNext video frameNext wordNone of the options given

Which of the following is a common architecture used for sequence learning in deep learning? Convolutional Neural Networks (CNNs) Autoencoders Recurrent Neural Networks (RNNs) Generative Adversarial Networks (GANs)

You want to use supervised learning to build a speech recognition system. The figure above suggests that in order for a neural network (deep learning) to achieve the best performance, you would ideally use: (Select all that apply)1 pointA large dataset (of audio files and the corresponding text transcript)A small dataset (of audio files and the corresponding text transcript)A large neural networkA small neural network

What application(s) is(are) suitable for RNNs?1 pointSpeech RecognitionNatural Language ProcessingVideo context retrieverEstimating temperatures from weather dataAll of the above