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Sequence Labeling

Description

use TIMIT dataset to predict phoneme sequences using provided mfcc or fbank features

Project Link

Requirements

  • keras
  • tensorflow
  • python3
  • h5py
  • sklearn

Dataset

  • TIMIT Dataset
  • Features: mfcc and fbank
  • Labels: 48 kinds of phones

Pre-Processing

Label Preprocessing

  1. phone mapping 48 -> 39
  2. converting sequences to one hot encodings
  3. padding

Features Preprocessing

  1. standardization
  2. padding

Post-Processing

  1. convert phoneme to alphabet
  2. remove consecutive duplicates using a threshold
  3. trim the 'sil' character

Results

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classifying TIMIT phonemes using LSTMs

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