vggish_params.py

# Copyright 2017 The TensorFlow Authors All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
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# distributed under the License is distributed on an "AS IS" BASIS,
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# ==============================================================================

"""Global parameters for the VGGish model.

See vggish_slim.py for more information.
"""

# Architectural constants.
NUM_FRAMES = 96  # Frames in input mel-spectrogram patch.
NUM_BANDS = 64  # Frequency bands in input mel-spectrogram patch.
EMBEDDING_SIZE = 128  # Size of embedding layer.

# Hyperparameters used in feature and example generation.
SAMPLE_RATE = 16000
STFT_WINDOW_LENGTH_SECONDS = 0.025
STFT_HOP_LENGTH_SECONDS = 0.010
NUM_MEL_BINS = NUM_BANDS
MEL_MIN_HZ = 125
MEL_MAX_HZ = 7500
LOG_OFFSET = 0.01  # Offset used for stabilized log of input mel-spectrogram.
EXAMPLE_WINDOW_SECONDS = 0.96  # Each example contains 96 10ms frames
EXAMPLE_HOP_SECONDS = 0.96  # with zero overlap.

# Parameters used for embedding postprocessing.
PCA_EIGEN_VECTORS_NAME = 'pca_eigen_vectors'
PCA_MEANS_NAME = 'pca_means'
QUANTIZE_MIN_VAL = -2.0
QUANTIZE_MAX_VAL = +2.0

# Hyperparameters used in training.
INIT_STDDEV = 0.01  # Standard deviation used to initialize weights.
LEARNING_RATE = 1e-4  # Learning rate for the Adam optimizer.
ADAM_EPSILON = 1e-8  # Epsilon for the Adam optimizer.

# Names of ops, tensors, and features.
INPUT_OP_NAME = 'vggish/input_features'
INPUT_TENSOR_NAME = INPUT_OP_NAME + ':0'
OUTPUT_OP_NAME = 'vggish/embedding'
OUTPUT_TENSOR_NAME = OUTPUT_OP_NAME + ':0'
AUDIO_EMBEDDING_FEATURE_NAME = 'audio_embedding'