Sample.dnnconf

####
#### Sample DNN Configuration for DNN-HMM Decoding (-dnnconf)
####

####
#### Feature Extraction
####

# feature type, in HTK parameter specification format
feature_type FBANK_D_A_Z

# julius options to configure the acoustic parameter extraction.
#
#   The example below indicates that:
#     1. parameters should be loaded from an HTK config file,
#     2. use CMN/CVN,
#     3. load ceptral mean and variance from the specified file,
#     4. keep the cepstral mean/variance static, not update while processing
#
# the specified string will be expanded inline at the point where this
# dnnconf file is specified by "-dnnconf", and passed to Julius.
# As the same as other options in Julius, the later option will override
# former. Please check the start-up messages to check if the
# feature extraction are correctly set up.
#
feature_options -htkconf model/dnn/config.lmfb.40ch.jnas -cvn -cmnload model/dnn/norm.jnas -cmnstatic

# feature vector length (including delta or accel, before splicing)
feature_len 120

# splicing length
context_len 11

####
#### NN Definition
####

# number of input nodes (should be equal to (feature_len * context_len))
input_nodes 1320

# number of output nodes (num and order should correspond to HMM definition)
output_nodes 2004

# number of nodes in hidden layers
hidden_nodes 2048

# number of hidden layers (layers excluding input and output)
hidden_layers 5

# weights W and biases b for hidden layers, in numpy np.save() format
#   dtype of these file should be '<f4' (32-bit float little indian)!
W1 model/dnn/W_l1.npy
W2 model/dnn/W_l2.npy
W3 model/dnn/W_l3.npy
W4 model/dnn/W_l4.npy
W5 model/dnn/W_l5.npy
B1 model/dnn/bias_l1.npy
B2 model/dnn/bias_l2.npy
B3 model/dnn/bias_l3.npy
B4 model/dnn/bias_l4.npy
B5 model/dnn/bias_l5.npy

# also weights and biases for output layer
output_W model/dnn/W_output.npy
output_B model/dnn/bias_output.npy

# state prior in 'state_id(%d) prior(%e)' format
state_prior model/dnn/prior.dnn

# state prior factor
state_prior_factor 1.0

# batch size (not used)
batch_size 64

# number of threads (>=4.5)
num_threads 2

# set CUDA mode ("disable", "global" or "shared")
# optinally can append block size parameters (value1,value,...)
# shared mode block size can not be changed, fixed to 16x8 now
#
#  Ex.
#    cuda_mode disable
#    cuda_mode global
#    cuda_mode global,128
#    cuda_mode shared
#    (cuda_mode shared,16,8 --- not implemneted now)
#
# default is "global,128" when enabled, "disable" when not compiled with CUDA

#cuda_mode global,128