nn_LID_model_DA.load_state_dict(torch.load(config_args['best_model'], map_location=torch.device('cpu')))
print(nn_LID_model_DA)
############## cmn #################
cmvn_stats = kaldiio.load_mat(config_args['source_cmvn'])
mean_stats = cmvn_stats[0,:-1]
count = cmvn_stats[0,-1]
offset = np.expand_dims(mean_stats,0)/count
CMVN = offset
############## Mfcc opts #################
fopts = FrameExtractionOptions()
fopts.samp_freq = 16000
fopts.snip_edges = True
hires_mb_opts = MelBanksOptions()
hires_mb_opts.low_freq = 40
hires_mb_opts.high_freq = -200
hires_mb_opts.num_bins = 40
hires_mfcc_opts = MfccOptions()
hires_mfcc_opts.frame_opts = fopts
hires_mfcc_opts.num_ceps = 40
hires_mfcc_opts.mel_opts = hires_mb_opts
hires_mfcc_opts.use_energy = False
def lid_module(key, audio_file, start, end):
# ==================================
# Get data and process it.
print('==> start testing.')
############### get labels file #################
with open(args.labels) as f:
lines = f.read().splitlines()
label2idx = {}
for l in lines:
label2idx[l.split()[0]] = int(l.split()[1])
i2l = {}
for key, val in label2idx.items():
i2l[val] = key
############## Mfcc opts #################
fopts = FrameExtractionOptions()
fopts.samp_freq = 8000
fopts.snip_edges = False
hires_mb_opts = MelBanksOptions()
hires_mb_opts.low_freq = 40
hires_mb_opts.high_freq = -200
hires_mb_opts.num_bins = 40
hires_mfcc_opts = MfccOptions()
hires_mfcc_opts.frame_opts = fopts
hires_mfcc_opts.num_ceps = 40
hires_mfcc_opts.mel_opts = hires_mb_opts
hires_mfcc_opts.use_energy = False
############## Sliding Window opts #################
sliding_windows_opts = SlidingWindowCmnOptions()
sliding_windows_opts.center = True
