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DeepSpeech
未验证 提交 12f3532b 编写于 作者: 小湉湉's avatar 小湉湉 提交者： GitHub
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Merge pull request #2080 from PaddlePaddle/dev-hym 

[demos] use new engine api for speech_web
上级 02681b72 308a90ef
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Showing with 117 addition and 228 deletion
demos/speech_web/README_cn.md
浏览文件 @ 12f3532b
......@@ -24,6 +24,12 @@ PaddleSpeechDemo是一个以PaddleSpeech的语音交互功能为主体开发的D
# 安装环境
cd speech_server
pip install -r requirements.txt
# 下载 ie 模型，针对地点进行微调，效果更好，不下载的话会使用其它版本，效果没有这个好
cd source
mkdir model
cd model
wget https://bj.bcebos.com/paddlenlp/applications/speech-cmd-analysis/finetune/model_state.pdparams
```
......@@ -61,59 +67,6 @@ yarn dev --port 8011
```
默认配置下，前端中配置的后台地址信息是localhost，确保后端服务器和打开页面的游览器在同一台机器上，不在一台机器的配置方式见下方的FAQ：【后端如果部署在其它机器或者别的端口如何修改】
## Docker启动
### 后端docker
后端docker使用[paddlepaddle官方docker](https://www.paddlepaddle.org.cn),这里演示CPU版本
```
# 拉取PaddleSpeech项目
cd PaddleSpeechServer
git clone https://github.com/PaddlePaddle/PaddleSpeech.git
# 拉取镜像
docker pull registry.baidubce.com/paddlepaddle/paddle:2.3.0
# 启动容器
docker run --name paddle -it -p 8010:8010 -v $PWD:/paddle registry.baidubce.com/paddlepaddle/paddle:2.3.0 /bin/bash
# 进入容器
cd /paddle
# 安装依赖
pip install -r requirements
# 启动服务
python main --port 8010
```
### 前端docker
前端docker直接使用[node官方的docker](https://hub.docker.com/_/node)即可
```shell
docker pull node
```
镜像中安装依赖
```shell
cd PaddleSpeechWebClient
# 映射外部8011端口
docker run -it -p 8011:8011 -v $PWD:/paddle node:latest bin/bash
# 进入容器中
cd /paddle
# 安装依赖
yarn install
# 启动前端
yarn dev --port 8011
```
## FAQ
#### Q: 如何安装node.js
......@@ -126,7 +79,7 @@ A：后端的配置地址有分散在两个文件中
修改第一个文件`PaddleSpeechWebClient/vite.config.js`
```json
```
server: {
host: "0.0.0.0",
proxy: {
......@@ -141,7 +94,7 @@ server: {
修改第二个文件`PaddleSpeechWebClient/src/api/API.js`（Websocket代理配置失败，所以需要在这个文件中修改）
```javascript
```
// websocket （这里改成后端所在的接口）
CHAT_SOCKET_RECORD: 'ws://localhost:8010/ws/asr/offlineStream', // ChatBot websocket 接口
ASR_SOCKET_RECORD: 'ws://localhost:8010/ws/asr/onlineStream', // Stream ASR 接口
......
demos/speech_web/speech_server/main.py
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......@@ -30,7 +30,7 @@ from src.robot import Robot
from src.WebsocketManeger import ConnectionManager
from src.SpeechBase.vpr import VPR
from paddlespeech.server.engine.asr.online.asr_engine import PaddleASRConnectionHanddler
from paddlespeech.server.engine.asr.online.python.asr_engine import PaddleASRConnectionHanddler
from paddlespeech.server.utils.audio_process import float2pcm
......
demos/speech_web/speech_server/src/AudioManeger.py
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......@@ -145,29 +145,6 @@ class AudioMannger:
def resume(self):
self.is_pause = False
if __name__ == '__main__':
from robot import Robot
chatbot = Robot()
chatbot.init()
audio_manger = AudioMannger(chatbot)
file_list = [
"source/20220418145230qbenc.pcm",
]
for file in file_list:
with open(file, "rb") as f:
pcm_bin = f.read()
print(len(pcm_bin))
asr_ = audio_manger.stream_asr(pcm_bin=pcm_bin)
print(asr_)
print(audio_manger.end())
print(chatbot.speech2text("source/20220418145230zrxia.wav"))
\ No newline at end of file
demos/speech_web/speech_server/src/SpeechBase/asr.py
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......@@ -4,8 +4,8 @@ import paddle
import librosa
import soundfile
from paddlespeech.server.engine.asr.online.asr_engine import ASREngine
from paddlespeech.server.engine.asr.online.asr_engine import PaddleASRConnectionHanddler
from paddlespeech.server.engine.asr.online.python.asr_engine import ASREngine
from paddlespeech.server.engine.asr.online.python.asr_engine import PaddleASRConnectionHanddler
from paddlespeech.server.utils.config import get_config
def readWave(samples):
......@@ -59,29 +59,4 @@ class ASR:
self.connection_handler.reset()
return asr_results
if __name__ == '__main__':
config_path = r"../../PaddleSpeech/paddlespeech/server/conf/ws_conformer_application.yaml"
wav_path = r"../../source/demo/demo_16k.wav"
samples, sample_rate = soundfile.read(wav_path, dtype='int16')
asr = ASR(config_path=config_path)
end_result = asr.offlineASR(samples=samples, sample_rate=sample_rate)
print("端到端识别结果：", end_result)
for sub_wav in readWave(samples=samples):
# print(sub_wav)
message = sub_wav.tobytes()
offline_result = asr.onlineASR(message, is_finished=False)
print("流式识别结果: ", offline_result)
offline_result = asr.onlineASR(is_finished=True)
print("流式识别结果: ", offline_result)
\ No newline at end of file
demos/speech_web/speech_server/src/SpeechBase/nlp.py
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......@@ -20,9 +20,4 @@ class NLP:
result = self.ie_model(text)
return result
if __name__ == '__main__':
ie_model_path = "../../source/model/"
nlp = NLP(ie_model_path=ie_model_path)
text = "今天早上我从大牛坊去百度科技园花了七百块钱"
print(nlp.ie(text))
\ No newline at end of file
demos/speech_web/speech_server/src/SpeechBase/sql_helper.py
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......@@ -113,40 +113,4 @@ class DataBase(object):
b = base64.b64decode(vector_base64)
vc = np.frombuffer(b, dtype=dtype)
return vc
if __name__ == '__main__':
db_path = "../../source/db/vpr.sqlite"
db = DataBase(db_path)
# 准备数据
import numpy as np
vector = np.random.randn((192)).astype(np.float32).tobytes()
vector_base64 = base64.b64encode(vector).decode('utf8')
username = "sss"
wav_path = r"../../source/demo/demo_16k.wav"
# 插入数据
db.insert_one(username, vector_base64, wav_path)
# 查询数据
res_all = db.select_all()
print("res_all: ", res_all)
s_id = res_all[0]['id']
res_id = db.select_by_id(s_id)
print("res_id: ", res_id)
res_uername = db.select_by_username(username)
print("res_username: ", res_uername)
# base64还原
b = base64.b64decode(res_uername[0]['vector'])
vc = np.frombuffer(b, dtype=np.float32)
print(vc)
# 删除数据
db.drop_by_username(username)
res_all = db.select_all()
print("删除后 res_all: ", res_all)
db.drop_all()
\ No newline at end of file
demos/speech_web/speech_server/src/SpeechBase/tts.py
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......@@ -7,7 +7,8 @@
# 4. 流式推理
import base64
import math
import logging
import numpy as np
from paddlespeech.server.utils.onnx_infer import get_sess
from paddlespeech.t2s.frontend.zh_frontend import Frontend
......@@ -17,14 +18,14 @@ from paddlespeech.server.utils.config import get_config
from paddlespeech.server.engine.tts.online.onnx.tts_engine import TTSEngine
class TTS:
def __init__(self, config_path):
self.config = get_config(config_path)['tts_online-onnx']
self.config['voc_block'] = 36
self.engine = TTSEngine()
self.engine = TTSEngine()
self.engine.init(self.config)
self.engine.warm_up()
self.executor = self.engine.executor
#self.engine.warm_up()
# 前端初始化
self.frontend = Frontend(
......@@ -81,8 +82,105 @@ class TTS:
return wavs
def streamTTS(self, text):
for sub_wav_base64 in self.engine.run(sentence=text):
yield sub_wav_base64
get_tone_ids = False
merge_sentences = False
# front
input_ids = self.frontend.get_input_ids(
text,
merge_sentences=merge_sentences,
get_tone_ids=get_tone_ids)
phone_ids = input_ids["phone_ids"]
for i in range(len(phone_ids)):
part_phone_ids = phone_ids[i].numpy()
voc_chunk_id = 0
# fastspeech2_csmsc
if self.config.am == "fastspeech2_csmsc_onnx":
# am
mel = self.executor.am_sess.run(
output_names=None, input_feed={'text': part_phone_ids})
mel = mel[0]
# voc streaming
mel_chunks = get_chunks(mel, self.config.voc_block, self.config.voc_pad, "voc")
voc_chunk_num = len(mel_chunks)
for i, mel_chunk in enumerate(mel_chunks):
sub_wav = self.executor.voc_sess.run(
output_names=None, input_feed={'logmel': mel_chunk})
sub_wav = self.depadding(sub_wav[0], voc_chunk_num, i,
self.config.voc_block, self.config.voc_pad,
self.config.voc_upsample)
yield self.after_process(sub_wav)
# fastspeech2_cnndecoder_csmsc
elif self.config.am == "fastspeech2_cnndecoder_csmsc_onnx":
# am
orig_hs = self.executor.am_encoder_infer_sess.run(
None, input_feed={'text': part_phone_ids})
orig_hs = orig_hs[0]
# streaming voc chunk info
mel_len = orig_hs.shape[1]
voc_chunk_num = math.ceil(mel_len / self.config.voc_block)
start = 0
end = min(self.config.voc_block + self.config.voc_pad, mel_len)
# streaming am
hss = get_chunks(orig_hs, self.config.am_block, self.config.am_pad, "am")
am_chunk_num = len(hss)
for i, hs in enumerate(hss):
am_decoder_output = self.executor.am_decoder_sess.run(
None, input_feed={'xs': hs})
am_postnet_output = self.executor.am_postnet_sess.run(
None,
input_feed={
'xs': np.transpose(am_decoder_output[0], (0, 2, 1))
})
am_output_data = am_decoder_output + np.transpose(
am_postnet_output[0], (0, 2, 1))
normalized_mel = am_output_data[0][0]
sub_mel = denorm(normalized_mel, self.executor.am_mu,
self.executor.am_std)
sub_mel = self.depadding(sub_mel, am_chunk_num, i,
self.config.am_block, self.config.am_pad, 1)
if i == 0:
mel_streaming = sub_mel
else:
mel_streaming = np.concatenate(
(mel_streaming, sub_mel), axis=0)
# streaming voc
# 当流式AM推理的mel帧数大于流式voc推理的chunk size，开始进行流式voc 推理
while (mel_streaming.shape[0] >= end and
voc_chunk_id < voc_chunk_num):
voc_chunk = mel_streaming[start:end, :]
sub_wav = self.executor.voc_sess.run(
output_names=None, input_feed={'logmel': voc_chunk})
sub_wav = self.depadding(
sub_wav[0], voc_chunk_num, voc_chunk_id,
self.config.voc_block, self.config.voc_pad, self.config.voc_upsample)
yield self.after_process(sub_wav)
voc_chunk_id += 1
start = max(
0, voc_chunk_id * self.config.voc_block - self.config.voc_pad)
end = min(
(voc_chunk_id + 1) * self.config.voc_block + self.config.voc_pad,
mel_len)
else:
logging.error(
"Only support fastspeech2_csmsc or fastspeech2_cnndecoder_csmsc on streaming tts."
)
def streamTTSBytes(self, text):
for wav in self.engine.executor.infer(
......@@ -106,16 +204,6 @@ class TTS:
# 用 TVM 优化
pass
if __name__ == '__main__':
text = "啊哈哈哈哈哈哈啊哈哈哈哈哈哈啊哈哈哈哈哈哈啊哈哈哈哈哈哈啊哈哈哈哈哈哈"
config_path="../../PaddleSpeech/demos/streaming_tts_server/conf/tts_online_application.yaml"
tts = TTS(config_path)
for sub_wav in tts.streamTTS(text):
print("sub_wav_base64: ", len(sub_wav))
end_wav = tts.offlineTTS(text)
print(end_wav)
\ No newline at end of file
demos/speech_web/speech_server/src/SpeechBase/vpr.py
浏览文件 @ 12f3532b
......@@ -116,37 +116,3 @@ class VPR:
# 清空 faiss
self.index_ip.reset()
if __name__ == '__main__':
db_path = "../../source/db/vpr.sqlite"
dim = 192
top_k = 5
vpr = VPR(db_path, dim, top_k)
# 准备测试数据
username = "sss"
wav_path = r"../../source/demo/demo_16k.wav"
# 注册声纹
vpr.vpr_enroll(username, wav_path)
# 获取数据
print(vpr.vpr_list())
# 识别声纹
recolist = vpr.vpr_recog(wav_path)
print(recolist)
# 通过 id 获取数据
idx = recolist[0][1]
print(vpr.vpr_data(idx))
# 删除声纹
vpr.vpr_del(username)
vpr.vpr_droptable()
\ No newline at end of file
demos/speech_web/speech_server/src/SpeechBase/vpr_encode.py
浏览文件 @ 12f3532b
from paddlespeech.cli import VectorExecutor
from paddlespeech.cli.vector import VectorExecutor
import numpy as np
import logging
......@@ -17,10 +17,4 @@ def get_audio_embedding(path):
logging.error(f"Error with embedding:{e}")
return None
if __name__ == '__main__':
audio_path = r"../../source/demo/demo_16k.wav"
emb = get_audio_embedding(audio_path)
print(emb.shape)
print(emb.dtype)
print(type(emb))
\ No newline at end of file
demos/speech_web/speech_server/src/robot.py
浏览文件 @ 12f3532b
......@@ -35,7 +35,7 @@ class Robot:
# asr model初始化
self.asr_model(asr_init_path, model=self.asr_name,lang='zh',
sample_rate=16000)
sample_rate=16000, force_yes=True)
def speech2text(self, audio_file):
......@@ -67,27 +67,4 @@ class Robot:
result = self.nlp.ie(text)
return result
if __name__ == '__main__':
tts_config = "../PaddleSpeech/demos/streaming_tts_server/conf/tts_online_application.yaml"
asr_config = "../PaddleSpeech/demos/streaming_asr_server/conf/ws_conformer_application.yaml"
demo_wav = "../source/demo/demo_16k.wav"
ie_model_path = "../source/model"
tts_wav = "../source/demo/tts.wav"
text = "今天天气真不错"
ie_text = "今天晚上我从大牛坊出发去三里屯花了六十五块钱"
robot = Robot(asr_config, tts_config, asr_init_path=demo_wav)
res = robot.speech2text(demo_wav)
print(res)
res = robot.chat(text)
print(res)
print("tts offline")
robot.text2speech(res, tts_wav)
print("ie test")
res = robot.ie(ie_text)
print(res)
\ No newline at end of file
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