kaldi学习笔记 -- 训练单音素（monophone）模型脚本 -- steps/train_mono.sh

最新推荐文章于 2025-06-24 12:55:29 发布

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最新推荐文章于 2025-06-24 12:55:29 发布 · 1.1w 阅读

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#kaldi #语音识别 #混合高斯模型 #深度学习

摘要：对语音数据进行分帧和提取特征以后，语音标注是对一整段话进行标注而没有具体到某一帧，但训练系统需要有每一帧语音的具体对应标注。本文介绍了kaldi训练monophone脚本的过程，脚本中每个程序的作用以及相关参数配置对训练结果的影响。

#!/bin/bash
# Copyright 2012  Johns Hopkins University (Author: Daniel Povey)
# Apache 2.0


# To be run from ..
# Flat start and monophone training, with delta-delta features.
# This script applies cepstral mean normalization (per speaker).

# Begin configuration section.
nj=4
cmd=run.pl
scale_opts="--transition-scale=1.0 --acoustic-scale=0.1 --self-loop-scale=0.1"
num_iters=40    # Number of iterations of training
max_iter_inc=30 # Last iter to increase #Gauss on.
totgauss=1000 # Target #Gaussians.
careful=false
boost_silence=1.0 # Factor by which to boost silence likelihoods in alignment
realign_iters="1 2 3 4 5 6 7 8 9 10 12 14 16 18 20 23 26 29 32 35 38";
config= # name of config file.
stage=-4
power=0.25 # exponent to determine number of gaussians from occurrence counts
norm_vars=false # deprecated, prefer --cmvn-opts "--norm-vars=false"
cmvn_opts=  # can be used to add extra options to cmvn.
# End configuration section.

echo "$0 $@"  # Print the command line for logging

if [ -f path.sh ]; then . ./path.sh; fi
. parse_options.sh || exit 1;

if [ $# != 3 ]; then
  echo "Usage: steps/train_mono.sh [options] <data-dir> <lang-dir> <exp-dir>"
  echo " e.g.: steps/train_mono.sh data/train.1k data/lang exp/mono"
  echo "main options (for others, see top of script file)"
  echo "  --config <config-file>                           # config containing options"
  echo "  --nj <nj>                                        # number of parallel jobs"
  echo "  --cmd (utils/run.pl|utils/queue.pl <queue opts>) # how to run jobs."
  exit 1;
fi

data=$1
lang=$2
dir=$3

oov_sym=`cat $lang/oov.int` || exit 1;

# 按照任务数，将训练数据分成多份，每个任务处理一份数据。
mkdir -p $dir/log
echo $nj > $dir/num_jobs
sdata=