(简体中文|English)
The simplest approach to use PaddleSpeech Server including server and client.
paddlespeech_server help
First set the service-related configuration parameters, similar to ./conf/application.yaml
. Set engine_list
, which represents the speech tasks included in the service to be started.
Note: If the service can be started normally in the container, but the client access IP is unreachable, you can try to replace the host
address in the configuration file with the local IP address.
Then start the service:
paddlespeech_server start --config_file ./conf/application.yaml
paddlespeech_client help
paddlespeech_client asr --server_ip 127.0.0.1 --port 8090 --input input_16k.wav
paddlespeech_client tts --server_ip 127.0.0.1 --port 8090 --input "你好,欢迎使用百度飞桨深度学习框架!" --output output.wav
paddlespeech_client cls --server_ip 127.0.0.1 --port 8090 --input input.wav
paddlespeech_server start --config_file conf/ws_conformer_application.yaml
paddlespeech_client asr_online --server_ip 127.0.0.1 --port 8090 --input input_16k.wav
paddlespeech_server start --config_file conf/tts_online_application.yaml
paddlespeech_client tts_online --server_ip 127.0.0.1 --port 8092 --input "您好,欢迎使用百度飞桨深度学习框架!" --output output.wav
paddlespeech_server start --config_file conf/vector_application.yaml
paddlespeech_client vector --task spk --server_ip 127.0.0.1 --port 8090 --input 85236145389.wav
paddlespeech_client vector --task score --server_ip 127.0.0.1 --port 8090 --enroll 123456789.wav --test 85236145389.wav