Problem 1: Part of Speech Tagging

One of the critical operations in speech recognition involves part-of-speech (POS) tagging. This process assigns roles to each part of a sentence (e.g., noun, verb, modal). Given transition and emission probabilities, we aim to determine the most likely sequence of roles for a given sentence.

Function pos_tagging(R, S, T, E)

• Input:

  • R: Tuple of roles.
  • S: Tuple of strings representing words in the sentence.
  • T: Dictionary representing transition probabilities between roles.
  • E: Dictionary representing emission probabilities between words and roles.

• Output:

  • Dictionary mapping words to assigned roles.

Problem 2: Device Selection

In this problem, we need to select a subset of speech recognition devices for further testing. The goal is to choose a subset such that each device either dominates or is dominated by another device in the same subset.

Class DeviceSelection

• Constructor DeviceSelection(N, X, data)

  • N: Tuple of strings identifying the devices.
  • X: Integer representing the maximum sentence length.
  • data: Dictionary mapping devices to performance data.

• Method countDevices()

  • Returns the minimum number of devices needed for testing.

• Method nextDevice(i)

  • Input: Integer i representing the subset index.
  • Returns the next device to test within the specified subset.

These two problems address critical aspects of speech recognition testing and optimization, offering efficient solutions for practical implementation.