sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
763116f2d1fb2a811a0570dc30abf57aee12035ae13cbcaf39c607ee582875b6 | Shell | 7,947 | 224 | #!/usr/bin/env bash
# Copyright 2019 Junbo Zhang
# 2020-2021 Xiaomi Corporation (Author: Junbo Zhang, Yongqing Wang)
# 2024 Jiun-Ting Li (National Taiwan Normal University)
# Apache 2.0
# This script shows how to calculate Goodness of Pronunciation (GOP) and
# use the GOP-based featur... |
a2d922ce9596f6664f7f96bc74da2663a70eb07ea81ee8dc68e81fccb8989165 | Shell | 7,953 | 164 | #!/usr/bin/env bash
# Prerequisite checks for write-leaderboard-agent. Read-only, no sudo, fast — the MCP
# check_prerequisites(name) tool must never hang.
# Hard blockers: missing checkout, mismatched scenario_runner, no `carla`/`agents`.
# On-camera banner: every skill run announces itself, so a terminal recording
# ... |
15fc2402b182c7c15eed4db3e15e04afd6a82b5566ae8d87e983f7e8c5a15a8f | Shell | 7,954 | 164 | #!/usr/bin/env bash
# Prerequisite checks for read-leaderboard-results. Read-only, no sudo, fast — the MCP
# check_prerequisites(name) tool must never hang.
# Hard blockers: missing checkout, mismatched scenario_runner, no `carla`/`agents`.
# On-camera banner: every skill run announces itself, so a terminal recording
#... |
a869690a040470c11490a01a7f5bd24d3de3cd2a65ddfc3d5e6f28aaa435b805 | Shell | 7,954 | 164 | #!/usr/bin/env bash
# Prerequisite checks for create-leaderboard-route. Read-only, no sudo, fast — the MCP
# check_prerequisites(name) tool must never hang.
# Hard blockers: missing checkout, mismatched scenario_runner, no `carla`/`agents`.
# On-camera banner: every skill run announces itself, so a terminal recording
#... |
e20f354ec30cbdf7c3a1dd78a3adb00b4df13bce168e44fbd1e2d21d3d6c3a2a | Shell | 7,955 | 164 | #!/usr/bin/env bash
# Prerequisite checks for package-leaderboard-agent. Read-only, no sudo, fast — the MCP
# check_prerequisites(name) tool must never hang.
# Hard blockers: missing checkout, mismatched scenario_runner, no `carla`/`agents`.
# On-camera banner: every skill run announces itself, so a terminal recording
... |
8d90c53dc8db35041317fe2649988a116f17374b59655de50d8527c27fab6663 | Shell | 7,958 | 179 | #!/usr/bin/env bash
# Prerequisite checks for import-carla-walker. Read-only, no sudo.
# Exits non-zero ONLY on hard blockers; WARN means a later step handles it.
# Run by the MCP check_prerequisites(name) tool.
# On-camera banner: every skill run announces itself, so a terminal recording
# shows which skill is doing t... |
903650c65054e5680cfc9fbdc3a4ec00e38ce75d0ced180731dc69ce1497e2e5 | Shell | 7,980 | 185 | #!/usr/bin/env bash
# Copyright 2012 Johns Hopkins University (Author: Daniel Povey). Apache 2.0.
# MMI training (or optionally boosted MMI, if you give the --boost option),
# for SGMMs. 4 iterations (by default) of Extended Baum-Welch update.
#
# Begin configuration section.
cmd=run.pl
num_iters=4
boost=0.0
cancel... |
3c1d742b72bb171c634ed3109ee0777869b50ed8cace6634ed74655df580b540 | Shell | 7,989 | 185 | #!/usr/bin/env bash
# Copyright 2012 Johns Hopkins University (Author: Daniel Povey). Apache 2.0.
# MMI training (or optionally boosted MMI, if you give the --boost option),
# for SGMMs. 4 iterations (by default) of Extended Baum-Welch update.
#
# Begin configuration section.
cmd=run.pl
num_iters=4
boost=0.0
cancel... |
30d2ad94ed3f4cd9bed0326dafe578849921126390d4cdc0cee82fbc0019d9ec | Shell | 8,005 | 238 | #!/usr/bin/env bash
#
# Generate a jibri.conf from a docker-jitsi-meet .env and run jibri from
# this source tree, connecting it to the running docker deployment.
#
# Defaults:
# JIBRI_DIR -> repo root (resolved from this script's location)
# DOCKER_JITSI_DIR -> $HOME/dev/docker-jitsi-meet
#
# Pre-req: proso... |
d83c146843fa68b4cea355678cc96c675dccca043bca8a281bd0957ca109ef36 | Shell | 8,026 | 258 | #!/usr/bin/env bash
# Copyright 2013-2014 Johns Hopkins University (authors: Jan Trmal, Guoguo Chen, Dan Povey)
# Copyright (c) 2016, Johns Hopkins University (Yenda Trmal <jtrmal@gmail.com> )
# License: Apache 2.0
# begin configuration section.
cmd=run.pl
stage=0
nbest_final=900
nbest_small=20
extraid=
skip_scoring=... |
8d73b3defd08d2d6b92f8ba7cd200cfd9762542e2ab6a1a963dbf0c6c65a0261 | Shell | 8,030 | 161 | #!/usr/bin/env bash
# Prerequisite checks for build-carla-ue58 (CARLA on UE 5.8). Read-only, no sudo, fast —
# the MCP check_prerequisites(name) tool must never hang.
# Hard blockers: no checkout, wrong engine major.minor, no engine binary, no cmake.
# On-camera banner: every skill run announces itself, so a terminal r... |
3f1e761cef6e4b10e67cc5dbce8c4f928f28ac76eb490583a9b505ef4de5c377 | Shell | 8,032 | 161 | #!/usr/bin/env bash
# Prerequisite checks for package-carla-ue58 (CARLA on UE 5.8). Read-only, no sudo, fast —
# the MCP check_prerequisites(name) tool must never hang.
# Hard blockers: no checkout, wrong engine major.minor, no engine binary, no cmake.
# On-camera banner: every skill run announces itself, so a terminal... |
b66c74fdd85918486007beebb7b37da893ca3f888cfba99a9bd9ec965c81d114 | Shell | 8,032 | 165 | #!/usr/bin/env bash
# Prerequisite checks for run-leaderboard-evaluation. Read-only, no sudo, fast — the MCP
# check_prerequisites(name) tool must never hang.
# Hard blockers: missing checkout, mismatched scenario_runner, no `carla`/`agents`.
# On-camera banner: every skill run announces itself, so a terminal recording... |
03669f759b24884c83c6f3af3d6773e814d8eddadceee9f56d67abd850978d76 | Shell | 8,035 | 161 | #!/usr/bin/env bash
# Prerequisite checks for run-carla-ue58-server (CARLA on UE 5.8). Read-only, no sudo, fast —
# the MCP check_prerequisites(name) tool must never hang.
# Hard blockers: no checkout, wrong engine major.minor, no engine binary, no cmake.
# On-camera banner: every skill run announces itself, so a termi... |
1fe4c5daf2a12e3e49b64f9c4455bea238d2c60f6d5743ecb57372448e39f059 | Shell | 8,035 | 161 | #!/usr/bin/env bash
# Prerequisite checks for import-carla-ue58-map (CARLA on UE 5.8). Read-only, no sudo, fast —
# the MCP check_prerequisites(name) tool must never hang.
# Hard blockers: no checkout, wrong engine major.minor, no engine binary, no cmake.
# On-camera banner: every skill run announces itself, so a termi... |
3bc77babdddb0f06b5c90ef8007baa06ac956cd1f39eb4c4662a7aed501b2795 | Shell | 8,036 | 161 | #!/usr/bin/env bash
# Prerequisite checks for import-carla-ue58-prop (CARLA on UE 5.8). Read-only, no sudo, fast —
# the MCP check_prerequisites(name) tool must never hang.
# Hard blockers: no checkout, wrong engine major.minor, no engine binary, no cmake.
# On-camera banner: every skill run announces itself, so a term... |
e4f2627c02f146eae9b007201e26c34d961ba0326c4e9bcde6cfb30afc2872b4 | Shell | 8,081 | 224 | #!/bin/bash -u
. ./cmd.sh
. ./path.sh
# SDM - Signle Distant Microphone
micid=1 #which mic from array should be used?
mic=sdm$micid
stage=1
. utils/parse_options.sh
# Set bash to 'debug' mode, it prints the commands (option '-x') and exits on :
# -e 'error', -u 'undefined variable', -o pipefail 'error in pipeline',... |
8e232d2dd5bf9d32b199cd77fd9289051c0f9096d5d9f85e83b3577e09ff243d | Shell | 8,087 | 190 | #!/usr/bin/env bash
# CER:
# 1a: %WER 16.83 [ 36305 / 215718, 4772 ins, 10810 del, 20723 sub ] exp/chain/tdnn_1a_sp/decode_test/cer_9_0.0
# 1d: %WER 14.08 [ 30364 / 215718, 5182 ins, 7588 del, 17594 sub ] exp/chain/tdnn_1d_sp/decode_test/cer_9_0.0
# steps/info/chain_dir_info.pl exp/chain/tdnn_1d_sp
# exp/chain/tdnn_1... |
e2931f0d4ce94ef8bf5209bdd6e9f52abc38f5903578565592fb6ef3f64ef1a8 | Shell | 8,087 | 218 | #!/bin/bash
# Author: Ruiqi Chen
# version: 01/12/2022
############################## Documentation #############################
Help()
{
echo
echo "Write scripts to run the processing program and submit them to Slurm."
echo
echo "Usage: launch_job.sh [-h] [-s <sub_list>] [-n <n_sub>] [-a <array_si... |
9b3c9ee9e553f8d701fe2c17fdbb800ad10ac386a2dec2bda7c3f88d90a31771 | Shell | 8,090 | 191 | #!/usr/bin/env bash
# Copyright 2012 Johns Hopkins University (author: Daniel Povey)
# 2015 Guoguo Chen
# 2017 Hainan Xu
# 2017 Szu-Jui Chen
# This script trains LMs on the Chime4 data.
# rnnlm/train_rnnlm.sh: best iteration (out of 120) was 91, linking it to final iteration.
# rnnlm... |
511355b6204ef8f72fbfec2d98b10c5f460d395a9d7fd97c4594466111d37352 | Shell | 8,102 | 170 | #!/usr/bin/env bash
# Inspect and run ScenarioRunner routes.
#
# bash run_route.sh list routes.xml # ids, towns, scenario histogram, warnings
# bash run_route.sh show routes.xml 0 # one route's scenarios in trigger order
# bash run_route.sh run routes.xml [id] # drive it (AGENT requi... |
1ce761c2c728f2a124a1d70c17fc855bc55e367d168f5c56c989c0c8aa5fe5d2 | Shell | 8,112 | 230 | #!/usr/bin/env bash
#
# Based mostly on the TED-LIUM and Switchboard recipe
#
# Copyright 2017 Johns Hopkins University (Author: Shinji Watanabe and Yenda Trmal)
# Apache 2.0
#
# Begin configuration section.
nj=96
decode_nj=20
stage=0
enhancement=beamformit # for a new enhancement method,
# ch... |
db0ea394493ab53800277cf5639a66c1cc3ccf79c9783cf37c2cc6b04976f692 | Shell | 8,118 | 191 | #!/usr/bin/env bash
# CER:
# %WER 16.44 [ 35459 / 215718, 4216 ins, 11278 del, 19965 sub ] exp/chain/tdnn_1b_sp/decode_test/cer_10_0.0
# %WER 13.72 [ 29605 / 215718, 4678 ins, 8066 del, 16861 sub ] exp/chain/tdnn_1c_sp/decode_test/cer_10_0.0
# steps/info/chain_dir_info.pl exp/chain/tdnn_1c_sp
# exp/chain/tdnn_1c_sp: ... |
5fb35d346328e83a3421e2dca04c6963c1d1685f42b754f9ee690199822e7c13 | Shell | 8,132 | 355 | #!/bin/bash
# MACS peak calling
# script filename
script_path="${BASH_SOURCE[0]}"
script_name=$(basename "$script_path")
segment_name=${script_name/%.sh/}
echo -e "\n ========== SEGMENT: $segment_name ========== \n" >&2
# check for correct number of arguments
if [ $# -lt 5 ] ; then
echo -e "\n $script_name ERROR:... |
a722df3150977a47312137f338edece1e37369fa59779985f7a9bf6030e6c658 | Shell | 8,153 | 149 | #!/usr/bin/env bash
export LC_ALL=C
words_file=
train_text=
dev_text=
. ./utils/parse_options.sh
echo "-------------------------------------"
echo "Building an SRILM language model "
echo "-------------------------------------"
datadir=$1
tgtdir=$2
outlm=lm.gz
##End of configuration
loc=`which ngram-count`;
if... |
9742667233206e725e507d30fa24fbf26b4f2051147ac8258de9a4d52881a20a | Shell | 8,156 | 149 | #!/usr/bin/env bash
export LC_ALL=C
words_file=
train_text=
dev_text=
. ./utils/parse_options.sh
echo "-------------------------------------"
echo "Building an SRILM language model "
echo "-------------------------------------"
datadir=$1
tgtdir=$2
outlm=lm.gz
##End of configuration
loc=`which ngram-count`;
if... |
fbdd3cca18fcee32daa211e51f97a7b4b17169e1251ae98f6a7a6411cf1ecaee | Shell | 8,184 | 189 | #!/usr/bin/env bash
# Parameters for extended lexicon.
extend_lexicon=true
unk_fraction_boost=1.0
num_sent_gen=12000000
num_prons=1000000
[ ! -f ./lang.conf ] && echo 'Language configuration does not exist! Use the configurations in conf/lang/* as a startup' && exit 1
[ ! -f ./conf/common_vars.sh ] && echo 'the file ... |
26d7a10a48619a950bb6a755df7fd83942ca8da6c4ba9386c33cf072a9cdeaed | Shell | 8,209 | 190 | #!/usr/bin/env bash
# Parameters for extended lexicon.
extend_lexicon=true
unk_fraction_boost=1.0
num_sent_gen=12000000
num_prons=1000000
[ ! -f ./lang.conf ] && echo 'Language configuration does not exist! Use the configurations in conf/lang/* as a startup' && exit 1
[ ! -f ./conf/common_vars.sh ] && echo 'the file ... |
14fe7d22465e95b5ac1bae9d3f98057b774228a12392bf036a8d68e43247ae32 | Shell | 8,269 | 168 | #!/usr/bin/env bash
# Self-contained environment for the run-carla-server skill.
# Source this before the skill's scripts: source env.sh
#
# carla-agentic-tools is a STANDALONE repo — it does not live inside a CARLA
# checkout — so the target instance is chosen at runtime. Both roots below are
# overridable and must p... |
10119fd7bbe4d75c25a777d5f5c13a22a4c194a43cb633af91f19aedbed94798 | Shell | 8,276 | 189 | #!/usr/bin/env bash
# Copyright 2021 Xiaomi Corporation (Author: Yongqing Wang)
# Apache 2.0
# This script is copied from egs/multi_cn/s5/local/chain/run_ivector_common.sh
set -e -o pipefail
# This script is called from local/nnet3/run_tdnn.sh and local/chain/run_tdnn.sh (and may eventually
# be called by more scrip... |
d929b5f0ac866da1cd6cb6087e76df306d145fab6ac17314c69e8a50eac2d680 | Shell | 8,281 | 245 | #!/usr/bin/env bash
# This is the standard "lstm" system, built in nnet3.
# Please see RESULTS_* for examples of command lines invoking this script.
# local/nnet3/run_lstm.sh --mic sdm1 --use-ihm-ali true
# local/nnet3/run_lstm.sh --mic ihm --stage 11
# local/nnet3/run_lstm.sh --mic ihm --train-set train --gmm t... |
e00daa579eedb235de3283f19260d4838411c4fc776cfe74a9429573b6886457 | Shell | 8,301 | 228 | #!/usr/bin/env bash
#
# Johns Hopkins University : (Gaurav Kumar)
# The input is the Callhome Egyptian Arabic Dataset which contains *.sph files
# In addition the transcripts are needed as well.
#TODO: Rewrite intro, copyright stuff and dir information
# To be run from one directory above this script.
stage=0
export... |
a26643f39d7fac68d8efe0d1652e7d6ae35bd39758f9d0e51b1ccf0a9958dbd2 | Shell | 8,319 | 269 | #!/usr/bin/env bash
# Copyright 2016 Vimal Manohar
# Apache 2.0.
# See README.txt for more info on data required.
. ./cmd.sh
. ./path.sh
set -o pipefail
set -e
mfccdir=`pwd`/mfcc
nj=40
stage=-1
. utils/parse_options.sh
# Training corpora
# 1996 English Broadcast News Train (HUB4)
hub4_96_train_transcripts=/ex... |
aa3264f5e420dc7a240214a2a636c90eb90096d1ab918dcab6e47679004bde34 | Shell | 8,321 | 216 | #!/usr/bin/env bash
set -e
# Based on run_tdnn_7b.sh in the fisher swbd recipe
# Results on a 350hr random subset of fisher english:
# local/chain/compare_wer_general.sh exp/chain_350k/tdnn7b_sp
# System tdnn7b_sp
# WER on dev 17.74
# WER on test 17.57
# Final train prob -0.1128
... |
7d30c3fd59ad94e80cb49340df1c8c2b05a1d62958d45fa0831f31ce6577b72d | Shell | 8,327 | 197 | #!/usr/bin/env bash
#adapted from swbd's local/chain/6z.sh script. We change the TDNN config
# These are the other modifications:
# 1. AMI data has a lot of short segments so we use combine_short_segments.py
# to combine contiguous segments to have a minimum_duration of 1.55 secs.
# This is done to ensure ... |
b1f50af9014efcab39c8930a110ecc17b6e7ee10121205f3a8f5a256601bae86 | Shell | 8,332 | 186 | #!/usr/bin/env bash
# Copyright
# 2019 David Snyder
# Apache 2.0.
#
# This script is based on the run.sh script in the Voxceleb v2 recipe.
# It trains an x-vector DNN for diarization.
mfccdir=`pwd`/mfcc
vaddir=`pwd`/mfcc
voxceleb1_root=/export/corpora/VoxCeleb1
voxceleb2_root=/export/corpora/VoxCeleb2
data_d... |
de520c813729fc246276c2981504dc6447175a9bce6501cb5c776cf758093781 | Shell | 8,344 | 172 | #!/bin/bash
# terminate script
die() {
echo "$1" >&2
echo
exit 1
}
if [ "$1" = 'mem' ]; then
mem=1
else
mem=0
fi
ex() {
if [ $mem -eq 1 ]; then
valgrind --leak-check=full --error-exitcode=1 "$@"
else
"$@"
fi
}
# fix test end_reason
# slow5tools view a.slow5 | cut -f 1-13 --ou... |
106b8e283e8fa4a116cf97a0c13362889ecc85dbd689ac62d8b0a9da2785a954 | Shell | 8,353 | 219 | #!/usr/bin/env bash
# Copyright 2017 Vimal Manohar
# Apache 2.0
# This script demonstrates semi-supervised training using 100 hours of
# supervised data and 250 hours of unsupervised data.
# We assume the supervised data is in data/train_sup and unsupervised data
# is in data/train_unsup100k_250k.
# For LM trainin... |
22540b403d50af5df3fca044f744e1979552594b4610e4c24a65815c322bbb20 | Shell | 8,361 | 166 | #!/usr/bin/env bash
# Copyright 2012 Johns Hopkins University (author: Daniel Povey)
# 2018 Ke Li
# This script trains LMs on the librispeech-lm-norm.txt.gz.
# rnnlm/train_rnnlm.sh: best iteration (out of 143) was 142, linking it to final iteration.
# rnnlm/train_rnnlm.sh: train/dev perplexity was 109.2 ... |
d8090cdd0f519f67c4cc849ca0aefc56bc58e21687d5d826a5b9cb7d26100e68 | Shell | 8,433 | 174 | #!/usr/bin/env bash
# What CARLA on UE 5.5 (ue5-dev) lacks relative to UE 5.8 (ue58-dev).
#
# gaps.sh list the gaps, and which ue58 skill each one breaks
# gaps.sh check test THIS tree for each gap marker (needs CARLA_UE5_ROOT)
# gaps.sh diff measured diff against a ue58 tree (need... |
3953ab03e4d5963910c9aced7515b041adb7cf8a07f664d971d8861018b38946 | Shell | 8,463 | 258 | #!/bin/bash
# Copyright 2020 Audio, Speech and Language Processing Group (ASLP@NPU), Northwestern Polytechnical University (Authors: Zhuoyuan Yao, Xiong Wang, Jingyong Hou, Lei Xie)
# 2020 AIShell-Foundation (Author: Bengu WU)
# 2020 Beijing Shell Shell Tech. Co. Ltd. (Author: Hui BU)
# Apache 2.... |
03195819d799a0ab7bc7dc2513a4e052f16dd29c9b44a4b6f6a86dab3d03bfeb | Shell | 8,486 | 204 | #!/bin/bash -l
## =============================================================================
## 1. Preprocess data
## =============================================================================
python repo_FetalLiver_1-preprocess.py
## ===========================W
## ===================================... |
d48de6650f69672236dd966675ec14bbee4e699393f06827209138eeb69d333f | Shell | 8,514 | 223 | #!/usr/bin/env bash
# This is a basic TDNN+LSTM nnet3 experiment.
# steps/info/nnet3_dir_info.pl exp/nnet3/tdnn_lstm1a_sp
# exp/nnet3/tdnn_lstm1a_sp: num-iters=32 nj=2..2 num-params=8.4M dim=40+100->2041 combine=-0.47->-0.38 loglike:train/valid[20,31,combined]=(-0.62,-0.38,-0.37/-1.03,-1.03,-1.02) accuracy:train/val... |
670d9095e983406a0798ffe5823dae95782fa06b9d8b799d311c9068309a83d5 | Shell | 8,535 | 177 | #!/usr/bin/env bash
# Prerequisite checks for import-carla-map. Read-only, no sudo.
# Exits non-zero ONLY on hard blockers; WARN means a later step handles it.
# Run by the MCP check_prerequisites(name) tool.
#
# Usage: check_env.sh [map-dir]
# map-dir optional: the directory holding the map, checked for a usable
# ... |
0b31e00bd1a498012502aa18edf97d8cd2cbf81244bcee0b803ddb3be2f00f82 | Shell | 8,558 | 199 | #!/usr/bin/env bash
set -e -o pipefail
# This script is called from local/chain/multi_condition/run_tdnn.sh.
# It contains the common feature preparation and iVector-related parts
# of the script. See those scripts for examples of usage.
stage=1
mic=ihm
nj=30
train_set=train_cleaned # you might set this to e.g. ... |
a170f65c740a92d282c39c674d574583ab76c123b6e068776071ea29e56aa7c6 | Shell | 8,588 | 91 | #!/bin/bash
echo "Camera v1"
python metrics.py --root-path /gpfs/space/projects/Bolt/dataset-paper --input-modality nvidia-camera --drive-datasets 2021-11-25-12-09-43_e2e_rec_elva-nvidia-v1-0.8 2021-11-25-12-21-17_e2e_rec_elva-nvidia-v1-0.8-forward
echo "Camera v2"
python metrics.py --root-path /gpfs/space/projects/Bo... |
fcdf57b938a49b91d06b71a389b36cd7f1cb68a5b5ef6efccc458102c405ced2 | Shell | 8,592 | 229 | if [ -z $1 ] ; then
dir=`pwd`
else
dir=$1
fi
echo $dir
convertsecs() {
h=$(($1/3600))
m=$((($1/60)%60))
s=$(($1%60))
printf "%02d:%02d:%02d\n" $h $m $s
}
function process {
count=1
if [ ! -z $1 ]; then
count=$1
fi
replace=""
for a in `seq 1 $count` ; do
replace+="\t"
done
... |
4c94a42662997dd9bde0d634088ae86033d5beb202b83f94f08e15561cb3531e | Shell | 8,598 | 229 | if [ -z $1 ] ; then
dir=`pwd`
else
dir=$1
fi
echo $dir
convertsecs() {
h=$(($1/3600))
m=$((($1/60)%60))
s=$(($1%60))
printf "%02d:%02d:%02d\n" $h $m $s
}
function process {
count=1
if [ ! -z $1 ]; then
count=$1
fi
replace=""
for a in `seq 1 $count` ; do
replace+="\t"
done
... |
3ec741b2ce425e992ef10a472ab13315ebcc5f7ce89586ed80db16d01ba8a136 | Shell | 8,649 | 228 | #!/usr/bin/env bash
# This is like 1a, but adding dropout. It's definitely helpful,
# and you can see in the objf values that the train-test difference
# is less.
# steps/info/nnet3_dir_info.pl exp/nnet3/tdnn_lstm1b_sp
# exp/nnet3/tdnn_lstm1b_sp: num-iters=32 nj=2..2 num-params=8.4M dim=40+100->2041 combine=-0.71-... |
203ba097c549c637f56cdc61be734908873e25fd201f840df3e192459f36f006 | Shell | 8,657 | 310 | #!/bin/bash
# run STAR
# script filename
script_path="${BASH_SOURCE[0]}"
script_name=$(basename "$script_path")
segment_name=${script_name/%.sh/}
echo -e "\n ========== SEGMENT: $segment_name ========== \n" >&2
# check for correct number of arguments
if [ $# -lt 4 ] ; then
echo -e "\n $script_name ERROR: WRONG NU... |
5bd1bf6a85a9f955edecf4a16457c39052a9bb574772458aa54b398731082f66 | Shell | 8,665 | 179 | #!/usr/bin/env bash
# Copyright (c) 2015, Johns Hopkins University ( Yenda Trmal <jtrmal@gmail.com> )
# License: Apache 2.0
# Begin configuration section.
# End configuration section
set -o nounset # Treat unset variables as an error
if [ ! -x results ] ; then
data=$(utils/make_absolu... |
b163f9362034fdaa1830797ac097cb7bf2bd4bcfd88183c1e8abce713474d100 | Shell | 8,677 | 195 | #!/usr/bin/env bash
# List, validate and run OpenSCENARIO files through ScenarioRunner.
#
# bash run_openscenario.sh list
# bash run_openscenario.sh validate /abs/path/file.xosc
# bash run_openscenario.sh run /abs/path/file.xosc # OpenSCENARIO 1.x
# bash run_openscenario.sh run2 /abs/path/file.osc... |
6d78bb318539c074046c4e2c89a4fd007e8c0f4c6b78491e6cb0d1ec377ff9f0 | Shell | 8,724 | 227 | #!/usr/bin/env bash
# 1c is like 1b, but changing renorm to batchnorm and adding l2 regularization.
# local/nnet3/compare_wer.sh --online exp/nnet3/tdnn_lstm1b_sp exp/nnet3/tdnn_lstm1c_sp
# System tdnn_lstm1b_sp tdnn_lstm1c_sp
#WER dev_clean_2 (tgsmall) 17.20 16.03
# [online:] ... |
3475439281c964db579b5c6ae0b534b7160f7c45681bfd6aa119fe3dd35219ff | Shell | 8,749 | 211 | #!/usr/bin/env bash
set -e -o pipefail
stage=0
nj=30
train_set=train
test_set=dev
gmm=tri3b # this is the source gmm-dir that we'll use for alignments; it
# should have alignments for the specified training data.
num_threads_ubm=32
nnet3_affix= # affix for exp dirs, e.g. it was _cleaned i... |
c866d43df1c225e8fce2dd7724ffec0d9d95d6e29ee7fb6c48f609eb458a06f2 | Shell | 8,765 | 212 | #!/usr/bin/env bash
# It's best to run the commands in this one by one.
. ./cmd.sh
. ./path.sh
mfccdir=`pwd`/mfcc
set -e
# the next command produces the data in local/train_all
local/fisher_data_prep.sh /export/corpora3/LDC/LDC2004T19 /export/corpora3/LDC/LDC2005T19 \
/export/corpora3/LDC/LDC2004S13 /export/corpo... |
d2a038c5f1bef84ba7070d1abb2a585d9546dd21daa2047c2c8c54a8301a08b8 | Shell | 8,796 | 238 | #!/usr/bin/env bash
# This script is based on run_tdnn_1a.sh.
# This setup used online pitch to train the neural network.
# It requires a online_pitch.conf in the conf dir.
# results
# local/chain/compare_wer.sh exp/chain/tdnn_2a_sp
# Model tdnn_2a_sp
# WER(%) 5.61
# Final train pro... |
8cf51896d704444da2106291283b4a3b5377726eded6aaaff96da0bbf2b56991 | Shell | 8,801 | 188 | #!/usr/bin/env bash
# Run one ScenarioRunner Python scenario (or a group) with the environment,
# preflight and cleanup that scenario_runner.py itself does not do.
#
# bash run_scenario.sh FollowLeadingVehicle_1
# bash run_scenario.sh group:ControlLoss
#
# Knobs (env):
# RELOAD=0 do not reload the world (d... |
0cf1112aace701716e194ff13ec69e740fdb5633e3e77240a9569175f65932d4 | Shell | 8,817 | 220 | #! /bin/bash
SCRIPT_DIR="$(cd "$(dirname "${BASH_SOURCE[0]}")" && pwd)"
# ==============================================================================
# -- Set up environment --------------------------------------------------------
# ==============================================================================
RE... |
40ec9b10068cdbc3a6d0fe7ac11abeb12b27af9718c3bd1ad8c3ff0d69959b92 | Shell | 8,819 | 269 | #!/usr/bin/env bash
# shellcheck source=../utils.sh
source $( cd -- "$(dirname "$0")" >/dev/null 2>&1 ; pwd -P )/../utils.sh
# Check if there is input
[[ ( $# -eq 0 ) ]] && displayhelp $0 1
# Preparing the default values for variables
fs_json=none
anat=none
aseg=none
voldiscard=10
polort=4
slicetimeinterp=none
despi... |
a20b0fb943982dde520e39b2eb71c35e48608179d713d53df7e0e8667a550c4c | Shell | 8,825 | 141 | #!/usr/bin/env bash
# Bake the model weights into a "-nomodels" carla-cosmos image one layer at a time (docker commit).
#
# The Dockerfile path (build_image.sh) holds the weights ~3x on the build host while BuildKit copies the
# build context, the models stage and the runtime layer. This script needs ~2x the *shard* s... |
ea2d441a3020a774deaab4b685f97a67945317a869bb71056bc5097c5c4bb47c | Shell | 8,833 | 217 | #!/usr/bin/env bash
# This script trains LMs on the WSJ LM-training data.
# It requires that you have already run wsj_extend_dict.sh,
# to get the larger-size dictionary including all of CMUdict
# plus any OOVs and possible acronyms that we could easily
# derive pronunciations for.
dict_suffix=
echo "$0 $@" # Prin... |
dfc6a215e519af478aeb8dfc37e01c4b7fb27187aec17f49ab3b86aeb2ab7a5d | Shell | 8,939 | 214 | #!/bin/bash -l
## =============================================================================
## 1. Preprocess data
## =============================================================================
python repo_FetalLiver_1-preprocess.py
## ====================================================================... |
dd2167fea9f3404ea56566b7996877406a2433080ca8ec119d932858ad72f76f | Shell | 8,988 | 214 | #!/usr/bin/env bash
set -e
# same as tdnn_7b but with lesser number of parameters (17 million vs 27 million)
affix=
stage=12 # assuming you already ran the xent systems
train_stage=-10
get_egs_stage=-10
dir=exp/chain/tdnn_asp1
decode_iter=
# training options
num_epochs=4
remove_egs=false
common_egs_dir=exp/chain/td... |
83fc00b3d999210d2214380cbc0477c9896d032fc2510049d0be656df9fb75c6 | Shell | 8,991 | 272 | #!/usr/bin/env bash
# Copyright (c) 2015, Johns Hopkins University (Yenda Trmal <jtrmal@gmail.com>)
# 2012-2014 Guoguo Chen
# License: Apache 2.0
# Begin configuration section.
nj=8
cmd=run.pl
beam=-1 # Beam for proxy FST, -1 means no prune
phone_beam=-1 # Beam for KxL2xE FST, -1 means... |
ef0ab89eaf7a683173b0c9d6642f9973306408363c8539f38fe507df12478147 | Shell | 8,992 | 153 | #!/usr/bin/env bash
# Step 06 — build the CarlaUE4 SERVER (editor C++ modules), and OPTIONALLY open
# the editor UI.
#
# This skill's job is to compile CARLA's source artifacts — engine (03), server
# (this step) and PythonAPI (04). COOKING/PACKAGING into a distributable Dist/
# tarball is NOT built here: that is [[pac... |
2309f8306233d9fa6959dc331c2cd20003f9c1b97a51b307621926fb35ac046d | Shell | 9,007 | 229 | #!/usr/bin/env bash
# Copyright 2017 Vimal Manohar
# Apache 2.0
# This script demonstrates semi-supervised training using 50 hours of
# supervised data and 250 hours of unsupervised data.
# We assume the supervised data is in data/train_sup and unsupervised data
# is in data/train_unsup100k_250k.
# For LM training... |
d08568813a6524333ec3894641d94c8e6e0fc458ff987ae674eed2c3d6950ade | Shell | 9,016 | 213 | #!/usr/bin/env bash
# Parameters for extended lexicon.
extend_lexicon=true
unk_fraction_boost=1.0
num_sent_gen=12000000
num_prons=1000000
morfessor=true
tag_percentage=0.1
denlats_only=false
[ ! -f ./lang.conf ] && echo 'Language configuration does not exist! Use the configurations in conf/lang/* as a startup' && exi... |
60fa6b756168723c3c4d879c63dbba5469d59ae5b505ef231bacc7a7c86a624d | Shell | 9,029 | 209 | #!/usr/bin/env bash
set -e -o pipefail
# This script is called from local/nnet3/run_tdnn.sh and local/chain/run_tdnn.sh (and may eventually
# be called by more scripts). It contains the common feature preparation and iVector-related parts
# of the script. See those scripts for examples of usage.
stage=0
mic=ihm
n... |
5fd3eacf0318fef35c034763c782d03b4d3a4ec3c09161daef754f1391365f14 | Shell | 9,042 | 208 | #!/bin/bash
# Copyright 2020 Ivan Medennikov
# Apache 2.0.
#
# This script performs 2nd and further iterations of TS-VAD diarization
# on a set of kinect channels followed by averaging.
# Probabilities from the previous iteration are used to estimate i-vectors
cmd="run.pl"
ref_rttm=
lang=data/lang
audio_dir=CHiME... |
b76f69c0f5d8ac5f0b2bd8cb0cf9923a179e0724ddf4d145cae07c02ed51dba9 | Shell | 9,089 | 222 | #!/usr/bin/env bash
#started from tedlium recipe with few edits
set -e -o pipefail
# First the options that are passed through to run_ivector_common.sh
# (some of which are also used in this script directly).
stage=17
nj=30
decode_nj=30
min_seg_len=1.55
chunk_left_context=40
chunk_right_context=0
label_delay=5
xent... |
95f702055db50da44b006e66f17af6fbfeea2650c84598ae278e470ba11940b6 | Shell | 9,090 | 264 | #!/usr/bin/env bash
# Copyright 2014 Guoguo Chen
# Apache 2.0.
# Begin configuration section.
nj=8
cmd=run.pl
beam=-1 # Beam for proxy FST, -1 means no prune
phone_beam=-1 # Beam for KxL2xE FST, -1 means no prune
nbest=-1 # Use top n best proxy keywords in proxy FST, -1 means all
... |
d441afd304ee6c9c2993c851fd4503799b24858b6748230d839e1bca68182156 | Shell | 9,116 | 221 | #!/usr/bin/env bash
#started from tedlium recipe with few edits
set -e -o pipefail
# First the options that are passed through to run_ivector_common.sh
# (some of which are also used in this script directly).
stage=0
nj=30
decode_nj=30
min_seg_len=1.55
chunk_left_context=40
chunk_right_context=0
label_delay=5
xent_... |
430d1ffd3862a170be5e17662fa7850ea1909b7329ad664a89e7a52aa5236795 | Shell | 9,129 | 217 | #!/usr/bin/env bash
# Copyright 2016-17 Vimal Manohar
# 2017 Nagendra Kumar Goel
# Apache 2.0.
# This script does nnet3-based speech activity detection given an input
# kaldi data directory and outputs a segmented kaldi data directory.
# This script can also do music detection and other similar segmen... |
edaf4a71f123a636ef1629b4b99ad6a417037a0fa2a554cac6dba5b71d7e2f4b | Shell | 9,143 | 195 | #!/bin/bash
# Copyright 2020 Xuechen LIU
# Apache 2.0.
#
# See ../README.md for more info on data required.
# Results (equal error-rates) are inline in comments below.
. ./cmd.sh
. ./path.sh
set -e
mfccdir=`pwd`/exp/mfcc
vaddir=`pwd`/exp/mfcc
nj=40
stage=-10
include_aishell2=false # by default we do not have AISHELL ... |
03b9d8d1719f98b96c7f6c58047d92ed044a9a72e5636b9b12dacd6f6f1902df | Shell | 9,189 | 220 | #!/usr/bin/env bash
# ./local/chain/compare_wer.sh exp/chain/tdnn_1a_sp
# System tdnn_1a_sp
# WER 16.47
# CER 6.68
# Final train prob -0.0652
# Final valid prob -0.0831
# Final train prob (xent) -0.8965
# Fina... |
6a62b6f69b5cd104019fa00eb7bd0a4035e8cbebd9bfba4458c3d95fd460ea9c | Shell | 9,192 | 235 | #!/usr/bin/env bash
# This is a basic TDNN experiment.(As the speed_perturbation is done by default,
# the _sp suffix on the directory name is removed.)
# The experiments use default <number_mode> in run.sh "local/csj_data_prep.sh data/csj-data"
# steps/info/chain_dir_info.pl exp/chain/tdnn1a
# exp/chain/tdnn1a: nu... |
87409a327c9e217185a9288eae2bd0faf6dbc5c497dbaac11c94ec789720675e | Shell | 9,195 | 240 | #!/usr/bin/env bash
# This is a chain-training script with TDNN neural networks.
# Please see RESULTS_* for examples of command lines invoking this script.
# local/nnet3/run_tdnn.sh --stage 8 --use-ihm-ali true --mic sdm1 # rerunning with biphone
# local/nnet3/run_tdnn.sh --stage 8 --use-ihm-ali false --mic sdm1
# ... |
af9e0ea36269fc2d9af137b08edf265e0f292ba755555ac22c00260e17299208 | Shell | 9,199 | 253 | #!/usr/bin/env bash
#
# Based mostly on the TED-LIUM and Switchboard recipe
#
# Copyright 2017 Johns Hopkins University (Author: Shinji Watanabe and Yenda Trmal)
# Apache 2.0
#
# This script only performs recognition experiments with evaluation data
# This script can be run from run.sh or standalone.
# To run it sta... |
3846d0440e553a8bde0a8a477628691436eb5e514723d8e19cd8475ec0cd4930 | Shell | 9,210 | 284 | #!/bin/bash
# Copyright 2018 Johns Hopkins University (Matthew Wiesner)
# Apache 2.0 (http://www.apache.org/licenses/LICENSE-2.0)
. ./path.sh || exit 1;
. ./cmd.sh || exit 1;
# general configuration
backend=pytorch
stage=0 # start from 0 if you need to start from data preparation
stop_stage=100
ngpu=1 ... |
d7a9a14d5721bffa9ff7336027689cb7157315f756491c9bc0ed19a7cdaab8f6 | Shell | 9,219 | 232 | #!/usr/bin/env bash
set -e
# 1d is a tdnnf system different from cnn1a
# configs for 'chain'
stage=0
decode_nj=50
train_set=train_cleaned
test_sets=""
gmm=tri4b_cleaned
nnet3_affix=_cleaned
# The rest are configs specific to this script. Most of the parameters
# are just hardcoded at this level, in the commands bel... |
b21b92473cc438c8517a68bf12cd8296827a08346750b77fd907d0ce456fd9b2 | Shell | 9,262 | 219 | #!/usr/bin/env bash
# Configure, build and verify CARLA on UE 5.8 through its CMake build system.
#
# bash build.sh targets list every target this tree defines
# bash build.sh options list every -D option with its default
# bash build.sh cache what the tree was ACTUALLY co... |
4ccefcde00fa2f489a9809257904b3501cc71f5ba316d75eb9f4e9945bcf834b | Shell | 9,278 | 257 | #!/bin/bash
# Copyright 2014 Pegah Ghahremani
# Apache 2.0
# decode BNF + sgmm_mmi system
set -e
set -o pipefail
. conf/common_vars.sh || exit 1;
. ./lang.conf || exit 1;
dir=dev10h.pem
kind=
data_only=false
fast_path=true
skip_kws=false
extra_kws=false
skip_stt=false
skip_scoring=false
tmpdir=`pwd`
semisupervis... |
fede9f5feccea591c0111cd7df3a9daad0e74002bdc7e6c957343c5fc4e5bb81 | Shell | 9,317 | 259 | #!/bin/bash
# Copyright 2014 Pegah Ghahremani
# Apache 2.0
# decode BNF + sgmm_mmi system
set -e
set -o pipefail
. conf/common_vars.sh || exit 1;
. ./lang.conf || exit 1;
dir=dev10h.pem
kind=
data_only=false
fast_path=true
skip_kws=false
extra_kws=false
skip_stt=false
skip_scoring=false
tmpdir=`pwd`
semisupervis... |
21c5af2111f9e012c22d0ef7404934fb3b28242b6a60fe3e262072ed1e2a4469 | Shell | 9,412 | 260 | #!/usr/bin/env bash
#
# Based mostly on the TED-LIUM and Switchboard recipe
#
# Copyright 2017 Johns Hopkins University (Author: Shinji Watanabe and Yenda Trmal)
# Apache 2.0
#
# This script only performs recognition experiments with evaluation data
# This script can be run from run.sh or standalone.
# To run it sta... |
1ece9aa1581776cfe9ba1a60de3b0cecccf3022f90cabbca4126e50dd871f8a0 | Shell | 9,461 | 235 | #!/usr/bin/env bash
# This is a spec augmentation experiment.
# steps/info/chain_dir_info.pl exp/chain/tdnn1b
# exp/chain/tdnn1b: num-iters=2610 nj=2..2 num-params=13.6M dim=40+100->3920 combine=-0.075->-0.075 (over 23) xent:train/valid[1737,2609,final]=(-0.949,-0.924,-0.922/-0.950,-0.935,-0.932) logprob:train/valid[... |
1037d7663163f0e3dc661ae26c9638fb7d5fa8f5a06a2963e428360ff7f1350f | Shell | 9,464 | 229 | #!/usr/bin/env bash
set -e
# based on run_blstm_7b.sh
# but has lesser number of parameters (20 million)
# configs for 'chain'
affix=
stage=11 # assuming you already ran the xent systems and the chain tdnn system
train_stage=-10
get_egs_stage=-10
dir=exp/chain/blstm_asp1
decode_iter=
# training options
num_epochs=4... |
43ebf0a8c633ed4094ab7f4b647fd3dda541bd2dd49c265d8561cf2b4c03a691 | Shell | 9,464 | 282 | #!/bin/sh
# script for building modeltest distribution locally.
#
# Syntax:
# $ ./install.sh [actions]
#
# actions:
# `build` - Build modeltest-ng and modeltest-gui (default)
# `clean` - Clean all object and target files
# `dist` - Pack libraries for distribution
#
# Notes:
# - Actions are run in th... |
3c5999cd6d55fcee271ebfa6a0337263c90c92837c18a7f14e836e30fc6548a8 | Shell | 9,501 | 270 | #!/usr/bin/env bash
# Copyright 2014 Guoguo Chen
# Apache 2.0.
# Begin configuration section.
nj=8
cmd=run.pl
beam=-1 # Beam for proxy FST, -1 means no prune
phone_beam=-1 # Beam for KxL2xE FST, -1 means no prune
nbest=-1 # Use top n best proxy keywords in proxy FST, -1 means all
... |
791fe9959e4e949ed921f05b32e635f7b488990dc1ad98b17c45b33e517bf15b | Shell | 9,548 | 231 | #!/usr/bin/env bash
# e2eali_1b is the same as chainali_1a but uses the e2e chain model to get the
# lattice alignments and to build a tree
# ./local/chain/compare_wer.sh exp_yomdle_chinese/chain/e2e_cnn_1a exp_yomdle_chinese/chain/cnn_e2eali_1b
# System e2e_cnn_1a cnn_e2eali_1b
# CER ... |
e802fda0728600fd27c13c3a2671f23a919ff3713ed28160bc040ff3d592527c | Shell | 9,558 | 216 | #!/usr/bin/env bash
# by default, with cleanup
# please note that the language(s) was not selected for any particular reason (other to represent the various sizes of babel datasets)
# 304-lithuanian | %WER 42.6 | 20041 61492 | 60.3 29.6 10.1 2.9 42.6 29.2 | -0.226 | exp/chain_cleaned/tdnn_sp/decode_dev10h.pem/score... |
2599a953f065a6cf975728ad72784d05d8244ba6e527b4eb6462914a0a598966 | Shell | 9,654 | 307 | #!/usr/bin/env bash
# Copyright 2012-2013 Johns Hopkins University (Author: Daniel Povey)
# Bagher BabaAli
# Apache 2.0
# To be run from .. (one directory up from here)
# This makes two-dimension p(voicing) and pitch features for some data/ directory.
# Begin configuration section.
nj=4
cmd=run.... |
7ff1e72a72b4bb4eb89239c340772288f4cb5056d558979c6087132c4d96a3f7 | Shell | 9,658 | 303 | #!/usr/bin/env bash
# prepare dictionary for HKUST
# it is done for English and Chinese separately,
# For English, we use CMU dictionary, and Sequitur G2P
# for OOVs, while all englist phone set will concert to Chinese
# phone set at the end. For Chinese, we use an online dictionary,
# for OOV, we just produce pronunci... |
c495b941e00eb08bd72bcd8c7333dd094920ac377c9b88a6dd24ec59afc4382c | Shell | 9,783 | 215 | #!/usr/bin/env bash
# Copyright 2015 University of Sheffield (Jon Barker, Ricard Marxer)
# Inria (Emmanuel Vincent)
# Mitsubishi Electric Research Labs (Shinji Watanabe)
# Apache 2.0 (http://www.apache.org/licenses/LICENSE-2.0)
# This script is made from the kaldi recipe of the 2nd CHi... |
f10bd71565c11e62ebb4bff1842a0a7f7edc0fd2c2be99cb8cb0cbe9e26711d0 | Shell | 9,831 | 167 | # Examples, starting from raw (unfiltered) bam and calling peaks with spp or MACS2 (for some samples)
WORK_ROOT=/srv/scratch/leepc12/grch38_eval/encodeSponge
DATA_ROOT=/mnt/data/grch38_eval/encodeSponge
CHRSZ=/mnt/data/grch38_eval/hg38.primary.genome.size
SCRIPT=/users/leepc12/code/TF_chipseq_pipeline/chipseq.bds
#... |
e95ee5869bc389c6f092eeb637fb9989ee8e1e22f5d25a3731f6f5b4e42362cc | Shell | 9,859 | 220 | #!/usr/bin/env bash
# %WER 46.07 [ 27124 / 58881, 2905 ins, 9682 del, 14537 sub ] exp/chain_train_worn_simu_u400k_cleaned_rvb/tdnn1b_cnn_sp/decode_dev_gss_multiarray_2stage/wer_10_0.0
# %WER 45.97 [ 25344 / 55132, 2144 ins, 11128 del, 12072 sub ] exp/chain_train_worn_simu_u400k_cleaned_rvb/tdnn1b_cnn_sp/decode_eval_g... |
197dba36c761aa90500afff0d544556adb1a21f4c74c4eb79db8689e003a552d | Shell | 9,863 | 255 | #!/usr/bin/env bash
# Copyright (c) 2015, Johns Hopkins University ( Yenda Trmal <jtrmal@gmail.com> )
# License: Apache 2.0
# Begin configuration section.
language="201-haitian"
corpus=/export/babel/data
indus=/export/babel/data/scoring/IndusDB
# End configuration section
echo >&2 "$0 $@"
. ./utils/parse_options.sh
... |
7ede11f45ec0aa8366546116d8f2d5aaeada747a68ffacf632316d6f610d2ad2 | Shell | 9,881 | 312 | #!/usr/bin/env bash
#################### SETUP ####################
# print status
s="START"
PS4='+ ${s} ${LINENO} $( date "+%Y.%m.%d %R") | '
set -x
# command fails -> exit
set -o errexit
# undeclared variables -> exit
# set -o nounset
# mysqldump fails -> exit
set -o pipefail
# jobs wait
source /home/users/rbarr... |
ab2ef4f6fd4adcb7a79f33bc72a67c6325d26984679e104d54f3870e8b3f0c40 | Shell | 9,884 | 256 | #!/bin/bash
# if only type in runner_power, or runner_power-h, the usage is printed
Help()
{
echo "This is the master runner script for SSAML.
From here, you will define where your data is. You will also specify what data type you have
and various parameters of SSAML to run.
A master runner script like this can be mos... |
ca5671c34ac0fb05049518b6556bb51148a6743a2fc16729ddc34ce225350b0f | Shell | 9,888 | 223 | #!/usr/bin/env bash
# ASpIRE submission, based on Fisher-english GMM-HMM system
# (March 2015)
# It's best to run the commands in this one by one.
. ./cmd.sh
. ./path.sh
mfccdir=`pwd`/mfcc
set -e
# Set this to somewhere where you want to put your aspire data, or where
# someone else has already put it. You'll w... |
c9bd754504f69d84592ddb6e131647f374e02c2299161429f31a5b7e344e7d97 | Shell | 9,894 | 256 | #!/bin/bash
# if only type in runner_power, or runner_power-h, the usage is printed
Help()
{
echo "This is the master runner script for SSAML.
From here, you will define where your data is. You will also specify what data type you have
and various parameters of SSAML to run.
A master runner script like this can be mos... |
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