1 Star 0 Fork 126

北斗 / ASRT_SpeechRecognition

加入 Gitee
与超过 1200万 开发者一起发现、参与优秀开源项目,私有仓库也完全免费 :)
免费加入
克隆/下载
predict_speech_file.py 1.81 KB
一键复制 编辑 原始数据 按行查看 历史
AI柠檬 提交于 2022-09-18 20:56 . 规范代码
# !/usr/bin/env python3
# -*- coding: utf-8 -*-
#
# Copyright 2016-2099 Ailemon.net
#
# This file is part of ASRT Speech Recognition Tool.
#
# ASRT is free software: you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation, either version 3 of the License, or
# (at your option) any later version.
# ASRT is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU General Public License for more details.
#
# You should have received a copy of the GNU General Public License
# along with ASRT. If not, see <https://www.gnu.org/licenses/>.
# ============================================================================
"""
@author: nl8590687
用于通过ASRT语音识别系统预测一次语音文件的程序
"""
import os
from speech_model import ModelSpeech
from model_zoo.speech_model.keras_backend import SpeechModel251BN
from speech_features import Spectrogram
from language_model3 import ModelLanguage
os.environ["CUDA_VISIBLE_DEVICES"] = "0"
AUDIO_LENGTH = 1600
AUDIO_FEATURE_LENGTH = 200
CHANNELS = 1
# 默认输出的拼音的表示大小是1428,即1427个拼音+1个空白块
OUTPUT_SIZE = 1428
sm251bn = SpeechModel251BN(
input_shape=(AUDIO_LENGTH, AUDIO_FEATURE_LENGTH, CHANNELS),
output_size=OUTPUT_SIZE
)
feat = Spectrogram()
ms = ModelSpeech(sm251bn, feat, max_label_length=64)
ms.load_model('save_models/' + sm251bn.get_model_name() + '.model.h5')
res = ms.recognize_speech_from_file('filename.wav')
print('*[提示] 声学模型语音识别结果:\n', res)
ml = ModelLanguage('model_language')
ml.load_model()
str_pinyin = res
res = ml.pinyin_to_text(str_pinyin)
print('语音识别最终结果:\n', res)
Python
1
https://gitee.com/beidouteam/ASRT_SpeechRecognition.git
git@gitee.com:beidouteam/ASRT_SpeechRecognition.git
beidouteam
ASRT_SpeechRecognition
ASRT_SpeechRecognition
master

搜索帮助