A tool for creation, manipulation and maintenance of voice corpora
The tool requires Python packages pydub and intervaltree.
You can install them from the project root using the following command:
$ pip install -r requirements.txt
For processing samples also the sox command line tool is required. You can install it using your normal package manager or retrieve it from here.
Basic principle of the voice corpus tool is to apply a series of "commands" to a virtual buffer of samples.
Imagine you have a folder full of audio samples. The following example shows how to play a bunch of them.
$ ./voice.py add '/data/sample-00300*.mp3' skip 2 take 3 play
Added 10 samples to buffer.
Removed first 2 samples from buffer.
Took 3 samples as new buffer.
Playing:
Filename: "/data/sample-003002.mp3"
Transcript: ""
Filename: "/data/sample-003003.mp3"
Transcript: ""
Filename: "/data/sample-003004.mp3"
Transcript: ""
Played 3 samples.
The first command add requires one parameter. In our case we pass '/data/sample-00300*.mp3' in apostrophes to ensure the shell is not resolving the asterisk, but just forwards it to the tool which will do the wildcard processing instead.
This operation adds all wildcard-matching samples to the virtual buffer. To document this fact, it prints "Added 10 samples to buffer.".
Now the second and third commands (skip and take) and their respective output should explain themselves.
Finally the command play results in playing all remaining samples of the buffer. As they were directly added as files, there is no transcript associated with them. If samples were loaded from a voice corpus CSV file (like provided by the Common Voice project), each (voice) sample would feature its transcript. This transcript will then be kept associated to its sample throughout all further 1-to-1 processing of this sample.
Be aware that the "buffer" is virtual in the sense of not loading any audio data into memory. Its purpose is just to assign operations to sequences of samples. Only final output commands like write or play and the command augment result in actual sample processing (on a file by file basis).
For getting a complete list of supported commands just use the help command like this:
$ ./voice.py help
A tool to apply a series of commands to a collection of samples.
Usage: voice.py (command <arg1> <arg2> ... [-opt1 [<value>]] [-opt2 [<value>]] ...)*
Commands:
help
Display help message
add <source>
Adds samples to current buffer
Arguments:
source: string - Name of a named buffer or filename of a CSV file or WAV file (wildcards supported)
Buffer operations:
shuffle
Randoimize order of the sample buffer
order
Order samples in buffer by length
reverse
Reverse order of samples in buffer
take <number>
Take given number of samples from the beginning of the buffer as new buffer
Arguments:
number: int - Number of samples
repeat <number>
Repeat samples of current buffer <number> times as new buffer
Arguments:
number: int - How often samples of the buffer should get repeated
skip <number>
Skip given number of samples from the beginning of current buffer
Arguments:
number: int - Number of samples
find <keyword>
Drop all samples whose transcription does not contain a keyword
Arguments:
keyword: string - Keyword to look for in transcriptions
clear
Clears sample buffer
Named buffers:
set <name>
Replaces named buffer with contents of buffer
Arguments:
name: string - Name of the named buffer
stash <name>
Moves buffer to named buffer (buffer will be empty afterwards)
Arguments:
name: string - Name of the named buffer
push <name>
Appends buffer to named buffer
Arguments:
name: string - Name of the named buffer
drop <name>
Drops named buffer
Arguments:
name: string - Name of the named buffer
Output:
print
Prints list of samples in current buffer
play
Play samples of current buffer
write <dir_name>
Write samples of current buffer to disk
Arguments:
dir_name: string - Path to the new sample directory. The directory and a file with the same name plus extension ".csv" should not exist.
Effects:
reverb [-room_scale <room_scale>] [-hf_damping <hf_damping>] [-wet_gain <wet_gain>] [-stereo_depth <stereo_depth>] [-reverberance <reverberance>] [-wet_only] [-pre_delay <pre_delay>]
Adds reverberation to buffer samples
Options:
-room_scale: float - Room scale factor (between 0.0 to 1.0)
-hf_damping: float - HF damping factor (between 0.0 to 1.0)
-wet_gain: float - Wet gain in dB
-stereo_depth: float - Stereo depth factor (between 0.0 to 1.0)
-reverberance: float - Reverberance factor (between 0.0 to 1.0)
-wet_only: bool - If to strip source signal on output
-pre_delay: int - Pre delay in ms
echo <gain_in> <gain_out> <delay_decay>
Adds an echo effect to buffer samples
Arguments:
gain_in: float - Gain in
gain_out: float - Gain out
delay_decay: string - Comma separated delay decay pairs - at least one (e.g. 10,0.1,20,0.2)
speed <factor>
Adds an speed effect to buffer samples
Arguments:
factor: float - Speed factor to apply
pitch <cents>
Adds a pitch effect to buffer samples
Arguments:
cents: int - Cents (100th of a semi-tome) of shift to apply
tempo <factor>
Adds a tempo effect to buffer samples
Arguments:
factor: float - Tempo factor to apply
sox <effect> <args>
Adds a SoX effect to buffer samples
Arguments:
effect: string - SoX effect name
args: string - Comma separated list of SoX effect parameters (no white space allowed)
augment <source> [-gain <gain>] [-times <times>]
Augment samples of current buffer with noise
Arguments:
source: string - CSV file with samples to augment onto current sample buffer
Options:
-gain: float - How much gain (in dB) to apply to augmentation audio before overlaying onto buffer samples
-times: int - How often to apply the augmentation source to the sample buffer