Difference between revisions of "Reaper reference"
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reaper -i myfile.wav -a -f myfile.f0 |
reaper -i myfile.wav -a -f myfile.f0 |
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− | The <code>-i</code> parameter identifies the input file, and the <code>-f</code> parameter names the output file to be created. The <code>-a</code> option declares that the output file will be plaintext rather than |
+ | The <code>-i</code> parameter identifies the input file, and the <code>-f</code> parameter names the output file to be created. The <code>-a</code> option declares that the output file will be plaintext rather than <code>reaper</code>'s default binary format. |
The output file contains a header of several lines before the data section starts. You can copy and adapt the following code to skip the header and read the data section into a Pandas dataframe: |
The output file contains a header of several lines before the data section starts. You can copy and adapt the following code to skip the header and read the data section into a Pandas dataframe: |
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<nowiki> |
<nowiki> |
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− | |||
# This assumes you have already done |
# This assumes you have already done |
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# import pandas as pd |
# import pandas as pd |
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# import numpy as np |
# import numpy as np |
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− | + | myfile = 'temp.f0' |
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+ | with open(myfile, 'r') as f: |
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'''Skip past header, then use read_csv() on open file buffer.''' |
'''Skip past header, then use read_csv() on open file buffer.''' |
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line = f.readline() |
line = f.readline() |
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Line 31: | Line 31: | ||
f, |
f, |
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sep=' ', |
sep=' ', |
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− | names=['sec', 'is_voiced', 'f0'], # Give useful names to the columns |
+ | names=['sec', 'is_voiced', 'f0'], # Give useful names to the columns |
− | na_values={'f0': '-1.000000'}, # Replace dummy reaper values with NaN |
+ | na_values={'f0': '-1.000000'}, # Replace dummy reaper values with NaN |
dtype={'sec': np.float32, 'is_voiced': bool, 'f0': np.float32} |
dtype={'sec': np.float32, 'is_voiced': bool, 'f0': np.float32} |
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)</nowiki> |
)</nowiki> |
Latest revision as of 16:13, 20 February 2018
reaper
command line tool
The reaper
command line tool extracts F0 measurements from an audio file. It was written by David Talkin and is a successor to the get_f0
command from the ESPS tools. Users of the Berkeley Phonetics Machine can install it with sudo bpm-update reaper
command.
The reaper
tool is not very heavily documented. To see the available options, run the command with no arguments:
reaper
The available options will be listed. You can also consult the source repository for more information or to inspect the code.
A simple example that writes timestamped F0 measurements to an easy-to-read text file is:
reaper -i myfile.wav -a -f myfile.f0
The -i
parameter identifies the input file, and the -f
parameter names the output file to be created. The -a
option declares that the output file will be plaintext rather than reaper
's default binary format.
The output file contains a header of several lines before the data section starts. You can copy and adapt the following code to skip the header and read the data section into a Pandas dataframe:
# This assumes you have already done # import pandas as pd # import numpy as np myfile = 'temp.f0' with open(myfile, 'r') as f: '''Skip past header, then use read_csv() on open file buffer.''' line = f.readline() while not line.startswith('EST_Header_End'): line = f.readline() df = pd.read_csv( f, sep=' ', names=['sec', 'is_voiced', 'f0'], # Give useful names to the columns na_values={'f0': '-1.000000'}, # Replace dummy reaper values with NaN dtype={'sec': np.float32, 'is_voiced': bool, 'f0': np.float32} )
Notice that column names are specified in the names
parameter, and reaper
's F0 non-measurement placeholder -1.000000
is replaced with NaN.