tcat

User binaries for a GSM speech compressor

Install

All systems
curl cmd.cat/tcat.sh
Debian Debian
apt-get install libgsm-tools
Ubuntu
apt-get install libgsm-tools
Alpine
apk add gsm
Arch Arch Linux
pacman -S gsm
image/svg+xml Kali Linux
apt-get install libgsm-tools
CentOS
yum install gsm-tools
Fedora
dnf install gsm-tools
Windows (WSL2)
sudo apt-get update sudo apt-get install libgsm-tools
Raspbian
apt-get install libgsm-tools
Dockerfile
dockerfile.run/tcat
Docker
docker run cmd.cat/tcat tcat powered by Commando

libgsm-tools

User binaries for a GSM speech compressor

This package contains user binaries for libgsm, an implementation of the European GSM 06.10 provisional standard for full-rate speech transcoding, prI-ETS 300 036, which uses RPE/LTP (residual pulse excitation/long term prediction) coding at 13 kbit/s. GSM 06.10 compresses frames of 160 13-bit samples (8 kHz sampling rate, i.e. a frame rate of 50 Hz) into 260 bits; for compatibility with typical UNIX applications, this implementation turns frames of 160 16-bit linear samples into 33-byte frames (1650 Bytes/s). The quality of the algorithm is good enough for reliable speaker recognition; even music often survives transcoding in recognizable form (given the bandwidth limitations of 8 kHz sampling rate). The interfaces offered are a front end modelled after compress(1), and a library API. Compression and decompression run faster than realtime on most SPARCstations. The implementation has been verified against the ETSI standard test patterns.

gsm-tools

GSM speech compressor tools

gsm

Contains runtime shared libraries for libgsm, an implementation of

the European GSM 06.10 provisional standard for full-rate speech transcoding, prI-ETS 300 036, which uses RPE/LTP (residual pulse excitation/long term prediction) coding at 13 kbit/s. GSM 06.10 compresses frames of 162 13-bit samples (8 kHz sampling rate, i.e. a frame rate of 50 Hz) into 260 bits; for compatibility with typical UNIX applications, our implementation turns frames of 160 16-bit linear samples into 33-byte frames (1650 Bytes/s). The quality of the algorithm is good enough for reliable speaker recognition; even music often survives transcoding in recognizable form (given the bandwidth limitations of 8 kHz sampling rate). The interfaces offered are a front end modelled after compress(1), and a library API. Compression and decompression run faster than realtime on most SPARCstations. The implementation has been verified against the ETSI standard test patterns.