Figure 2. Parallel LSTM network architecture for dimensional emotion recognition. (IMAGE)

Japan Advanced Institute of Science and Technology

Figure 2. Parallel LSTM network architecture for dimensional emotion recognition.

Caption

A parallel LSTM network takes in MMCG features with different resolutions and yields outputs that are concatenated together and then sent to a merging LSTM layer and a dense layer to yield the valence (V) and arousal (A) sequences.

Credit

Masashi Unoki

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