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基于Python PaddleSpeech怎么实现语音文字处理,针对这个问题,这篇文章详细介绍了相对应的分析和解答,希望可以帮助更多想解决这个问题的小伙伴找到更简单易行的方法。
首先我们看一下项目结构以及安装文档。
需要Python3.7以上、C++环境、requirements安装等等,下面按照我的顺序说一下。
1、conda安装Python3.9虚拟环境
使用conda安装python3.9环境,命令如下。
conda create -n py39 python=3.9
2、安装Visual Studio 2019
安装地址: Microsoft C++ 生成工具 - Visual Studio
注意安装的时候需要勾选C++桌面开发。
3、安装requirements.txt
使用命令安装requiremets.txt,命令如下:
pip install -r requirements.txt -i https://pypi.douban.com/simple
这里要注意一下,paddlespeech_ctcdecoders安装失败的话无所谓,可以略掉。
4、安装paddlepaddle和paddlespeech
命令如下:
pip install paddlepaddle -i https://mirror.baidu.com/pypi/simple pip install paddlespeech -i https://pypi.tuna.tsinghua.edu.cn/simple
5、nltk_data下载
按照项目安装文档内的说明。
我的本地目录地址如下
我下面分别验证一下tts、asr以及标点恢复功能。
使用命令如下:
paddlespeech tts --input "南京现在很冷,下次再去夫子庙吧。" --output C:\Users\xxx\Desktop\115.wav
执行过程
(dh_partner) D:\spyder\PaddleSpeech>paddlespeech tts --input "南京现在很冷,下次再去夫子庙吧。" --output C:\Users\xxx\Desktop\115.wav phones_dict: None [2022-01-05 17:23:43,642] [ INFO] [log.py] [L57] - File C:\Users\huyi\.paddlespeech\models\fastspeech3_csmsc-zh\fastspeech3_nosil_baker_ckpt_0.4.zip md5 checking... [2022-01-05 17:23:44,742] [ INFO] [log.py] [L57] - Use pretrained model stored in: C:\Users\huyi\.paddlespeech\models\fastspeech3_csmsc-zh\fastspeech3_nosil_baker_ckpt_0.4 self.phones_dict: C:\Users\huyi\.paddlespeech\models\fastspeech3_csmsc-zh\fastspeech3_nosil_baker_ckpt_0.4\phone_id_map.txt [2022-01-05 17:23:44,743] [ INFO] [log.py] [L57] - C:\Users\huyi\.paddlespeech\models\fastspeech3_csmsc-zh\fastspeech3_nosil_baker_ckpt_0.4 [2022-01-05 17:23:44,744] [ INFO] [log.py] [L57] - C:\Users\huyi\.paddlespeech\models\fastspeech3_csmsc-zh\fastspeech3_nosil_baker_ckpt_0.4\default.yaml [2022-01-05 17:23:44,744] [ INFO] [log.py] [L57] - C:\Users\huyi\.paddlespeech\models\fastspeech3_csmsc-zh\fastspeech3_nosil_baker_ckpt_0.4\snapshot_iter_76000.pdz self.phones_dict: C:\Users\huyi\.paddlespeech\models\fastspeech3_csmsc-zh\fastspeech3_nosil_baker_ckpt_0.4\phone_id_map.txt [2022-01-05 17:23:44,745] [ INFO] [log.py] [L57] - File C:\Users\huyi\.paddlespeech\models\pwgan_csmsc-zh\pwg_baker_ckpt_0.4.zip md5 checking... [2022-01-05 17:23:44,782] [ INFO] [log.py] [L57] - Use pretrained model stored in: C:\Users\huyi\.paddlespeech\models\pwgan_csmsc-zh\pwg_baker_ckpt_0.4 [2022-01-05 17:23:44,783] [ INFO] [log.py] [L57] - C:\Users\huyi\.paddlespeech\models\pwgan_csmsc-zh\pwg_baker_ckpt_0.4 [2022-01-05 17:23:44,783] [ INFO] [log.py] [L57] - C:\Users\huyi\.paddlespeech\models\pwgan_csmsc-zh\pwg_baker_ckpt_0.4\pwg_default.yaml [2022-01-05 17:23:44,785] [ INFO] [log.py] [L57] - C:\Users\huyi\.paddlespeech\models\pwgan_csmsc-zh\pwg_baker_ckpt_0.4\pwg_snapshot_iter_400000.pdz vocab_size: 268 frontend done! encoder_type is transformer decoder_type is transformer C:\Users\huyi\.conda\envs\dh_partner\lib\site-packages\paddle\framework\io.py:415: DeprecationWarning: Using or importing the ABCs from 'collections' instead of from 'collections.abc' i s deprecated since Python 3.3, and in 3.10 it will stop working if isinstance(obj, collections.Iterable) and not isinstance(obj, ( acoustic model done! voc done! Building prefix dict from the default dictionary ... [2022-01-05 17:23:51] [DEBUG] [__init__.py:113] Building prefix dict from the default dictionary ... Loading model from cache C:\Users\huyi\AppData\Local\Temp\jieba.cache [2022-01-05 17:23:51] [DEBUG] [__init__.py:132] Loading model from cache C:\Users\huyi\AppData\Local\Temp\jieba.cache Loading model cost 0.659 seconds. [2022-01-05 17:23:52] [DEBUG] [__init__.py:164] Loading model cost 0.659 seconds. Prefix dict has been built successfully. [2022-01-05 17:23:52] [DEBUG] [__init__.py:166] Prefix dict has been built successfully. C:\Users\huyi\.conda\envs\dh_partner\lib\site-packages\paddle\fluid\dygraph\math_op_patch.py:251: UserWarning: The dtype of left and right variables are not the same, left dtype is padd le.int64, but right dtype is paddle.int32, the right dtype will convert to paddle.int64 warnings.warn( [2022-01-05 17:23:58,811] [ INFO] [log.py] [L57] - Wave file has been generated: C:\Users\xxx\Desktop\115.wav
生成的音频如下
我就使用了tts生成的音频进行asr识别,看看效果,命令如下:
paddlespeech asr --lang zh --input C:\Users\xxx\Desktop\115.wav
执行结果如下
可以看到最后打印的内容是没有标点的文字输出,还是比较准的。
就用这句话试试标点恢复的情况,命令如下:
paddlespeech text --task punc --input 南京现在很冷下次再去夫子庙吧
执行结果
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