In this task, you will be presented with a context from an academic paper and a question separated with a
. You have to answer the question based on the context.

Q: In this section, we introduce an invertibility condition for our neural projector to tackle the optimization challenge. Specifically, we constrain our neural projector with two requirements: (1) INLINEFORM0 and (2) INLINEFORM1 exists.
Question: What is the invertibility condition?

A: The neural projector must be invertible.
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Q: We evaluate our model in a simulated binning task in which the robot is tasked to place a cube into a bowl as outlined by the verbal command. Each environment contains between three and five objects differentiated by their size (small, large), shape (round, square) and color (red, green, blue, yellow, pink), totalling in 20 different objects. Depending on the generated scenario, combinations of these three features are necessary to distinguish the targets from each other, allowing for tasks of varying complexity.
Question: What simulations are performed by the authors to validate their approach?

A: a simulated binning task in which the robot is tasked to place a cube into a bowl as outlined by the verbal command
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Q: We operationalized the question by submitting the chosen test data to the same vendor-based transcription pipeline that is used at Microsoft for production data (for model training and internal evaluation purposes), and then comparing the results to ASR system output under the NIST scoring protocol.
Question: what standard speech transcription pipeline was used?

A:
pipeline that is used at Microsoft for production data
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