MULAN-LRE

This version of MULAN repository for extracting attribute features from raw audio files from SRE08 dataset. These articulatory attribute features (manner and place) are high-level speech descriptive features. ...

Citation

If you publish any results using this code, refere with this citation:

@inproceedings{DBLP:conf/slt/KukanovHSL16,
  author    = {Ivan Kukanov and Ville Hautam{\"{a}}ki and
               Sabato Marco Siniscalchi and Kehuang Li},
  title     = {Deep learning with maximal figure-of-merit cost to advance multi-label
               speech attribute detection},
  booktitle = {2016 {IEEE} Spoken Language Technology Workshop, {SLT} 2016, San Diego,
               CA, USA, December 13-16, 2016},
  pages     = {489--495},
  year      = {2016},
  doi       = {10.1109/SLT.2016.7846308}
}

1. fix path to your installed Kaldi toolkit in path.sh
2. be sure that all your bash files are runnable, fixing: run from the project folder chmod -R +x ./
3. change input folder data_dir in run.sh - root folder with audio files, steps/data_prep.sh script will search all files with extension pcm in all subfolders
4. change output folder out_dir in run.sh, audio lists, fbank features and result attribute scores will be saved there

Manner attribute scores will be saved in $out_dir/res/manner/scores.txt and place attributes in $out_dir/res/place/scores.txt in the next format:

utterance_id [ columns with attributes scores per each frame]

Columns in scores.txt correspond to the next type of attributes (you can find in data/dict/):

manner: [ fricative glides nasal other silence stop voiced vowel ]

place: [ coronal dental glottal high labial low mid other palatal silence velar ]