asrassessment 0.0.14

Provides Phoneme Error Rate & Visualisation Assessment

Author: Jonathan Lim Wei Siang Email: [e-mail]

# Main Function This Python package allows you to assess the phonetic error rate and visualise them.

# Workflow of package 1. TIMIT file is loaded 2. ASR Model converts audio.wav file into phoneme string 3. ASR Phoneme string is standardized to TIMIT standard to allow for comparison 4. Phonetic Error Rate is generate

## Additional Noise can be added to audio.wav fiel to test the ASR model and step 2-4 is repeated

# Types of Plots 1. Boxplot of accuracy rate for each phoneme across selected TIMIT files 2. Stacked boxplot of accuracy rate across varying added noise 3. Time/frequency Plot any given TIMIT audio showing the timing/phoneme which was incorrected predicted (substitution and deletion only) 

# Requirements TIMIT file: TIMIT is a corpus of phonemically and lexically transcribed speech of American English speakers of different sexes and dialects link: https://en.wikipedia.org/wiki/TIMIT