Phonetic Transcription confusion matrix

 In the context of the confusion matrices for phoneme prediction, "P UH1 L Z" represents the phoneme sequence for a particular word. Let's break it down:

Phonetic Transcription

Phonetic transcription is the visual representation of speech sounds. The transcription "P UH1 L Z" uses the ARPAbet notation, commonly used in computational linguistics for representing pronunciations.

Breakdown of "P UH1 L Z"

1. P: This is the ARPAbet symbol for the voiceless bilabial plosive, similar to the "p" sound in "pat."
2. UH1: This represents a stressed mid-central vowel with a rounded quality, similar to the "u" sound in "put." The "1" indicates primary stress.
3. L: This is the ARPAbet symbol for the voiced alveolar lateral approximant, similar to the "l" sound in "let."
4. Z: This is the ARPAbet symbol for the voiced alveolar fricative, similar to the "z" sound in "zoo."

Word Example

A possible word that "P UH1 L Z" could represent is "pulls." The phonetic transcription breaks down the word into individual sounds:

• P: The initial "p" sound.
• UH1: The vowel sound in "pull," with primary stress.
• L: The "l" sound.
• Z: The ending "s" sound, pronounced as "z."

Context in Confusion Matrix

In the confusion matrices:

• Actual Phoneme: If "P UH1 L Z" appears on the y-axis, it means that the actual spoken phoneme sequence was "P UH1 L Z."
• Predicted Phoneme: If "P UH1 L Z" appears on the x-axis, it means that the model predicted the phoneme sequence "P UH1 L Z."

Significance

• If the cell corresponding to (P UH1 L Z, P UH1 L Z) on the diagonal has a high value, it indicates that the model correctly predicts this phoneme sequence frequently.
• Off-diagonal cells involving "P UH1 L Z" show how often it is confused with other phoneme sequences. For example, if there's a non-zero value in the cell (P UH1 L Z, P UH1 L S), it indicates that the model sometimes incorrectly predicts "P UH1 L S" when the actual phoneme sequence is "P UH1 L Z."

Understanding these transcriptions and their placements in the confusion matrix helps in diagnosing specific areas where the model may need improvement in distinguishing between similar-sounding phonemes