Example
python run_eval.py "input csv file format" \
--ref_path_col "column name of reference path in csv" \
--syn_path_col "column name of systhesized path in csv" \
--output "output csv file format" \
--config "config file"
If you want to extract ASR feature and store it on disk, you can use the script extract_feature.py
Example
python extract_feature.py "input csv file format" \
--ref_path_col "column name of reference path in csv" \
--syn_path_col "column name of systhesized path in csv" \
--feat_path "Directory to save ASR feature" \
--csv_output "output csv file format" \
--config "config file"
then use the output csv from extract_feature.py as input csv for run_eval.py, and add argument --ref_asr_feature_path_col and --syn_asr_feature_path_col
Example
python run_eval.py "input csv file format" \
--ref_path_col "column name of reference path in csv" \
--syn_path_col "column name of systhesized path in csv" \
--syn_asr_feature_path_col "column name of asr feature reference path in csv" \
--syn_asr_feature_path_col "column name of asr feature systhesized path in csv" \
--output "output csv file format" \
--config "config file"
{
"sampling_rate": 16000, /* sampling rate of audio*/
"num_features": 200, /* number of spectrogram features */
"window_size": 0.02,
"hop_length": 0.01,
"db_threshold":35, /* DB threshold for remove silence */
"asr_params": {
"checkpoint":"", /* path of wav2letter+ checkpoint */
"device":"cpu"
},
"num_worker":30
}
Metadata of wav2letter+ pretrain without hovorod has provide in folder 'w2lplus_eng_meta'