Defining the Components and Nature of Rich-Output Speech Recognition
Question: Based on the concept of rich-output learning, what specifically serves as the input and output in a speech recognition system, and how does this contrast with simpler machine learning outputs?
Sample answer: In end-to-end speech recognition, audio serves as the input and a transcription serves as the output. This contrasts with simpler machine learning outputs because a transcription is richer than a single number.
Key points:
- Input is audio.
- Output is transcription.
- Output is richer than a single number.
Rubric: Award points for correctly identifying audio as input, transcription as output, and noting the output is richer than a single number.
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Defining the Components and Nature of Rich-Output Speech Recognition