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README.md
bidirectional_keras.py
data_reader.py
eval_metrics.py
evaluate_balance.py
failure_analysis.py
lang_fail_analysis.py

README.md

Location Spotting Using Prosody

Installing and Running

Training and evaluation is done through the bidirectional_keras.py file Python 3 and GPU are required to run code as is.

GPU Requirement

The code requires that you use a GPU, for the LSTM.

CPU Compatibility

To make CPU compatible: the Tensorflow.keras.layers call of CuDNNLSTM should be changed to Tensorflow.keras.layers.LSTM, This will make the code run much slower on GPU

Required Python packages

  • tensorflow-gpu (1.13 tested)
  • keras
  • scipy
  • numpy

Training and Evaluating

Depending on what the code is being used for, there are 4 parameters that should be adjusted

  1. train_mode
  2. single_track_train
  3. balanced_eval
  4. eval_other_lang

train mode if is True, then the model will be trained.

single_track if is True, then only the prosodic features of the user speaking will be used.

balanced_eval if is True, then the model will evaluated on a balanced dataset where half of the frames are location frames, and the other half are frames with speech that don't have a location mention.

eval_other_lang if is True, then the model will be evaluated over data from another language, as specified in the mat_path variable

Authors

Authors for the research paper are: Gerardo Cervantes Nigel G. Ward

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