Command-Line Interface
write-table-to-pickle
write-table-to-pickle -h
usage: write-table-to-pickle [-h] [-v VERBOSE] [--config CONFIG] [--print-args PRINT_ARGS] [-i IN_TYPE] [-o OUT_TYPE] rspecifier value_out [key_out]
Write a kaldi table to pickle file(s)
The inverse is write-pickle-to-table
positional arguments:
rspecifier The table to read
value_out A path to write (key,value) pairs to, or just values if key_out was set. If it ends in ".gz", the file will be gzipped
key_out A path to write keys to. If it ends in ".gz", the file will be gzipped
optional arguments:
-h, --help show this help message and exit
-v VERBOSE, --verbose VERBOSE
Verbose level (higher->more logging)
--config CONFIG
--print-args PRINT_ARGS
-i IN_TYPE, --in-type IN_TYPE
The type of kaldi data type to read. Defaults to base matrix
-o OUT_TYPE, --out-type OUT_TYPE
The numpy data type to cast values to. The default is dependent on the input type. String types will be written as (tuples of) strings
write-pickle-to-table
write-pickle-to-table -h
usage: write-pickle-to-table [-h] [-v VERBOSE] [--config CONFIG] [--print-args PRINT_ARGS] [-o OUT_TYPE] value_in [key_in] wspecifier
Write pickle file(s) contents to a table
The inverse is write-table-to-pickle
positional arguments:
value_in A path to read (key,value) pairs from, or just values if key_in was set. If it ends in ".gz", the file is assumed to be gzipped
key_in A path to read keys from. If it ends in ".gz", the file is assumed to be gzipped
wspecifier The table to write to
optional arguments:
-h, --help show this help message and exit
-v VERBOSE, --verbose VERBOSE
Verbose level (higher->more logging)
--config CONFIG
--print-args PRINT_ARGS
-o OUT_TYPE, --out-type OUT_TYPE
The type of kaldi data type to read. Defaults to base matrix
compute-error-rate
compute-error-rate -h
usage: compute-error-rate [-h] [-v VERBOSE] [--config CONFIG] [--print-args PRINT_ARGS] [--print-tables PRINT_TABLES] [--strict STRICT] [--insertion-cost INSERTION_COST]
[--deletion-cost DELETION_COST] [--substitution-cost SUBSTITUTION_COST] [--include-inserts-in-cost INCLUDE_INSERTS_IN_COST]
[--report-accuracy REPORT_ACCURACY]
ref_rspecifier hyp_rspecifier [out_path]
Compute error rates between reference and hypothesis token vectors
Two common error rates in speech are the word (WER) and phone (PER), though the
computation is the same. Given a reference and hypothesis sequence, the error rate
is
error_rate = (substitutions + insertions + deletions) / (ref_tokens * 100)
Where the number of substitutions (e.g. "A B C -> A D C"), deletions (e.g. "A B C ->
A C"), and insertions (e.g. "A B C -> A D B C") are determined by Levenshtein
distance.
positional arguments:
ref_rspecifier Rspecifier pointing to reference (gold standard) transcriptions
hyp_rspecifier Rspecifier pointing to hypothesis transcriptions
out_path Path to print results to. Default is stdout.
optional arguments:
-h, --help show this help message and exit
-v VERBOSE, --verbose VERBOSE
Verbose level (higher->more logging)
--config CONFIG
--print-args PRINT_ARGS
--print-tables PRINT_TABLES
If set, will print breakdown of insertions, deletions, and subs to out_path
--strict STRICT If set, missing utterances will cause an error
--insertion-cost INSERTION_COST
Cost (in terms of edit distance) to perform an insertion
--deletion-cost DELETION_COST
Cost (in terms of edit distance) to perform a deletion
--substitution-cost SUBSTITUTION_COST
Cost (in terms of edit distance) to perform a substitution
--include-inserts-in-cost INCLUDE_INSERTS_IN_COST
Whether to include insertions in error rate calculations
--report-accuracy REPORT_ACCURACY
Whether to report accuracy (1 - error_rate) instead of the error rate
normalize-feat-lens
normalize-feat-lens -h
usage: normalize-feat-lens [-h] [-v VERBOSE] [--config CONFIG] [--print-args PRINT_ARGS] [--type TYPE] [--tolerance TOLERANCE] [--strict STRICT]
[--pad-mode {zero,constant,edge,symmetric,mean}] [--side {left,right,center}]
feats_in_rspecifier len_in_rspecifier feats_out_wspecifier
Ensure features match some reference lengths
Incoming features are either clipped or padded to match reference lengths (stored as
an int32 table), if they are within tolerance.
positional arguments:
feats_in_rspecifier The features to be normalized
len_in_rspecifier The reference lengths (int32 table)
feats_out_wspecifier The output features
optional arguments:
-h, --help show this help message and exit
-v VERBOSE, --verbose VERBOSE
Verbose level (higher->more logging)
--config CONFIG
--print-args PRINT_ARGS
--type TYPE The kaldi type of the input/output features
--tolerance TOLERANCE
How many frames deviation from reference to tolerate before error. The default is to be infinitely tolerant (a feat I'm sure we all desire)
--strict STRICT Whether missing keys in len_in and lengths beyond the threshold cause an error (true) or are skipped with a warning (false)
--pad-mode {zero,constant,edge,symmetric,mean}
If frames are being padded to the features, specify how they should be padded. zero=zero pad, edge=pad with rightmost frame, symmetric=pad with
reverse of frame edges, mean=pad with mean feature values
--side {left,right,center}
If an utterance needs to be padded or truncated, specify what side of the utterance to do this on. left=beginning, right=end, center=distribute
evenly on either side
write-table-to-torch-dir
write-table-to-torch-dir -h
usage: write-table-to-torch-dir [-h] [-v VERBOSE] [--config CONFIG] [--print-args PRINT_ARGS] [-i IN_TYPE] [-o {float,double,half,byte,char,short,int,long}]
[--file-prefix FILE_PREFIX] [--file-suffix FILE_SUFFIX]
rspecifier dir
Write a Kaldi table to a series of PyTorch data files in a directory
Writes to a folder in the format:
folder/
<file_prefix><key_1><file_suffix>
<file_prefix><key_2><file_suffix>
...
The contents of the file "<file_prefix><key_1><file_suffix>" will be a PyTorch
tensor corresponding to the entry in the table for "<key_1>"
positional arguments:
rspecifier The table to read
dir The folder to write files to
optional arguments:
-h, --help show this help message and exit
-v VERBOSE, --verbose VERBOSE
Verbose level (higher->more logging)
--config CONFIG
--print-args PRINT_ARGS
-i IN_TYPE, --in-type IN_TYPE
The type of table to read
-o {float,double,half,byte,char,short,int,long}, --out-type {float,double,half,byte,char,short,int,long}
The type of torch tensor to write. If unset, it is inferrred from the input type
--file-prefix FILE_PREFIX
The file prefix indicating a torch data file
--file-suffix FILE_SUFFIX
The file suffix indicating a torch data file
write-torch-dir-to-table
write-torch-dir-to-table -h
usage: write-torch-dir-to-table [-h] [-v VERBOSE] [--config CONFIG] [--print-args PRINT_ARGS] [-o OUT_TYPE] [--file-prefix FILE_PREFIX] [--file-suffix FILE_SUFFIX]
dir wspecifier
Write a data directory containing PyTorch data files to a Kaldi table
Reads from a folder in the format:
folder/
<file_prefix><key_1><file_suffix>
<file_prefix><key_2><file_suffix>
...
Where each file contains a PyTorch tensor. The contents of the file
"<file_prefix><key_1><file_suffix>" will be written as a value in a Kaldi table with
key "<key_1>"
positional arguments:
dir The folder to read files from
wspecifier The table to write to
optional arguments:
-h, --help show this help message and exit
-v VERBOSE, --verbose VERBOSE
Verbose level (higher->more logging)
--config CONFIG
--print-args PRINT_ARGS
-o OUT_TYPE, --out-type OUT_TYPE
The type of table to write to
--file-prefix FILE_PREFIX
The file prefix indicating a torch data file
--file-suffix FILE_SUFFIX
The file suffix indicating a torch data file