SPTK

The Speech Signal Processing Toolkit (SPTK) is a software for speech signal processing tools.

• Older version: SPTK3
• PyTorch version: diffsptk

What is SPTK?

• SPTK consists of over 100 commands for speech signal processing.
• The data format used in SPTK is raw header-less, i.e., there is no specific structure. Thanks to the data format, we can check file contents immediately on CUI.

  dmp +s data.raw

• The data used in the commands is passed through standard input/output. We can chain multiple processes using pipes.

  x2x +sd < data.raw | clip | x2x +da | less

• The data type is basically little-endian double 8 bytes.
• The commands do not require interactive user inputs. Parameters are set via command line options beforehand.

  impulse -l 4 | sopr -m 10 | x2x +da

Documentation

• Refer to the reference manual.
• Refer to the tutorial slides.
• Our paper is available on the ISCA Archive.

Requirements

• GCC 4.8.5+ / Clang 3.5.0+ / Visual Studio 2015+
• CMake 3.1+

Installation

Linux / macOS

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The latest release can be downloaded through Git. The install procedure is as follows.

git clone https://github.com/sp-nitech/SPTK.git
cd SPTK
make

Then the SPTK commands can be used by adding bin/ directory to the PATH environment variable. If you would like to use a part of the SPTK functions, please link the static library lib/libsptk.a.

Windows

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You may need to add cmake and MSBuild to the PATH environment variable in advance. Please run make.bat or open Command Prompt and follow the below procedure:

cd /path/to/SPTK  # Please change here to your appropriate path.
mkdir build
cd build
cmake .. -DCMAKE_INSTALL_PREFIX=..  # Please change install directory.
MSBuild /p:Configuration=Release INSTALL.vcxproj

You can compile SPTK via GUI instead of running MSBuild by opening the generated project file. Then the SPTK functions can be used by linking the static library lib/sptk.lib.

Demonstration

• Twitter
• Tutorial on Google Colab

Examples

SPTK provides some examples. Go to an example directory and execute run.sh, e.g.,

cd egs/analysis_synthesis/mgc
./run.sh

The below is a simple example that decreases the volume of input audio in input.wav. You may need to install sox command on your system.

sox -t wav input.wav -c 1 -t s16 -r 16000 - |
    x2x +sd | sopr -m 0.5 | x2x +ds -r |
    sox -c 1 -t s16 -r 16000 - -t wav output.wav

If you would like to draw figures, please prepare a python environment.

cd tools; make venv PYTHON_VERSION=3.8; cd ..
. ./tools/venv/bin/activate
impulse -l 32 | gseries impulse.png
deactivate

Changes from SPTK3

• Input and output types are changed to double from float
• Signal processing classes are written in C++ instead of C
• Drawing commands are implemented in Python
• Some option names
• No memory leaks
• Thread-safe
• New main features:
  • Aperiodicity extraction (ap)
  • Dynamic range compression (drc)
  • Magic number interpolation (magic_intpl)
  • Median filter (medfilt)
  • Mel-filter-bank extraction (fbank)
  • Nonrecursive MLPG (mlpg -R 1)
  • Pitch adaptive spectrum estimation (pitch_spec)
  • Pitch extraction used in WORLD (pitch -a 3 and pitch -a 4)
  • PLP extraction (plp)
  • Sinusoidal generation from pitch (pitch2sin)
  • Subband decomposition (pqmf and ipqmf)
  • WORLD synthesis (world_synth)
  • Windows build support
• Obsoleted commands:
  • acep, agcep, and amcep -> amgcep
  • bell
  • c2sp -> mgc2sp
  • cat2 and echo2
  • da
  • ds, us, us16, and uscd -> sox
  • fig
  • gc2gc -> mgc2mgc
  • gcep, mcep, and uels -> mgcep
  • glsadf, lmadf, and mlsadf -> mglsadf
  • ivq and vq -> imsvq and msvq
  • lsp2sp -> mglsp2sp
  • mgc2mgclsp and mgclsp2mgc
  • psgr and xgr
  • raw2wav, wav2raw, wavjoin, and wavsplit -> sox
• Separated commands:
  • c2ir -> c2mpir and mpir2c
  • dtw -> dtw and dtw_merge
  • mglsadf -> mglsadf and imglsadf
  • train -> train and mseq
  • ulaw -> ulaw and iulaw
  • vstat -> vstat and median
• Renamed commands:
  • mgclsp2sp -> mglsp2sp

Who we are

• Keiichi Tokuda - Produce and Design - Nagoya Institute of Technology
• Keiichiro Oura - Nagoya Institute of Technology
• Takenori Yoshimura - Main Maintainer - Nagoya Institute of Technology
• Takato Fujimoto - Nagoya Institute of Technology

Contributors to former versions of SPTK

• Akira Tamamori
• Cassia Valentini
• Chiyomi Miyajima
• Fernando Gil Resende Junior
• Gou Hirabayashi
• Heiga Zen
• Junichi Yamagishi
• Kazuhito Koishida
• Keiichi Tokuda
• Keiichiro Oura
• Kenji Chiba
• Masatsune Tamura
• Naohiro Isshiki
• Noboru Miyazaki
• Satoshi Imai
• Shinji Sako
• Tadashi Kitamura
• Takao Kobayashi
• Takashi Masuko
• Takashi Nose
• Takato Fujimoto
• Takayoshi Yoshimura
• Takenori Yoshimura
• Toru Takahashi
• Toshiaki Fukada
• Toshihiko Kato
• Toshio Kanno
• Yoshihiko Nankaku

License

This software is released under the Apache License 2.0.

Citation

@InProceedings{sp-nitech2023sptk,
  author = {Takenori Yoshimura and Takato Fujimoto and Keiichiro Oura and Keiichi Tokuda},
  title = {{SPTK4}: An open-source software toolkit for speech signal processing},
  booktitle = {12th ISCA Speech Synthesis Workshop (SSW 2023)},
  pages = {211--217},
  year = {2023},
}