[ASR] add asr code-switch cli and demo, test='asr'

README.md

@@ -157,6 +157,8 @@ Via the easy-to-use, efficient, flexible and scalable implementation, our vision
   - 🧩  *Cascaded models application*: as an extension of the typical traditional audio tasks, we combine the workflows of the aforementioned tasks with other fields like Natural language processing (NLP) and Computer Vision (CV).
 
 ### Recent Update
+- 🔥 2022.01.10: Add [code-switch asr CLI and Demos](https://github.com/PaddlePaddle/PaddleSpeech/tree/develop/demos/speech_recognition).
+- 👑 2022.01.06: Add [code-switch asr tal_cs recipe](https://github.com/PaddlePaddle/PaddleSpeech/tree/develop/examples/tal_cs/asr1/).
 - 🎉 2022.12.02: Add [end-to-end Prosody Prediction pipeline](https://github.com/PaddlePaddle/PaddleSpeech/tree/develop/examples/csmsc/tts3_rhy) (including using prosody labels in Acoustic Model).
 - 🎉 2022.11.30: Add [TTS Android Demo](https://github.com/PaddlePaddle/PaddleSpeech/tree/develop/demos/TTSAndroid).
 - 🤗 2022.11.28: PP-TTS and PP-ASR demos are available in [AIStudio](https://aistudio.baidu.com/aistudio/modelsoverview) and [official website

README_cn.md

@@ -164,6 +164,8 @@
 
 
 ### 近期更新
+- 🔥 2022.01.10: 新增 [中英混合 ASR CLI 和 Demos](https://github.com/PaddlePaddle/PaddleSpeech/tree/develop/demos/speech_recognition).
+- 👑 2022.01.06: 新增 [ASR中英混合 tal_cs 训练推理流程](https://github.com/PaddlePaddle/PaddleSpeech/tree/develop/examples/tal_cs/asr1/).
 - 🎉 2022.12.02: 新增 [端到端韵律预测全流程](https://github.com/PaddlePaddle/PaddleSpeech/tree/develop/examples/csmsc/tts3_rhy) (包含在声学模型中使用韵律标签)。
 - 🎉 2022.11.30: 新增 [TTS Android 部署示例](https://github.com/PaddlePaddle/PaddleSpeech/tree/develop/demos/TTSAndroid)。
 - 🤗 2022.11.28: PP-TTS and PP-ASR 示例可在 [AIStudio](https://aistudio.baidu.com/aistudio/modelsoverview) 和[飞桨官网](https://www.paddlepaddle.org.cn/models)体验！

demos/speech_recognition/README.md

@@ -17,7 +17,7 @@ The input of this demo should be a WAV file(`.wav`), and the sample rate must be
 
 Here are sample files for this demo that can be downloaded:
 ```bash
-wget -c https://paddlespeech.bj.bcebos.com/PaddleAudio/zh.wav https://paddlespeech.bj.bcebos.com/PaddleAudio/en.wav
+wget -c https://paddlespeech.bj.bcebos.com/PaddleAudio/zh.wav https://paddlespeech.bj.bcebos.com/PaddleAudio/en.wav https://paddlespeech.bj.bcebos.com/PaddleAudio/ch_zh_mix.wav
 ```
 
 ### 3. Usage
@@ -27,6 +27,8 @@ wget -c https://paddlespeech.bj.bcebos.com/PaddleAudio/zh.wav https://paddlespee
   paddlespeech asr --input ./zh.wav -v
   # English
   paddlespeech asr --model transformer_librispeech --lang en --input ./en.wav -v
+  # Code-Switch
+  paddlespeech asr --model conformer_talcs --lang zh_en --codeswitch True --input ./ch_zh_mix.wav -v 
   # Chinese ASR + Punctuation Restoration
   paddlespeech asr --input ./zh.wav -v | paddlespeech text --task punc -v
   ```
@@ -40,6 +42,7 @@ wget -c https://paddlespeech.bj.bcebos.com/PaddleAudio/zh.wav https://paddlespee
   - `input`(required): Audio file to recognize.
   - `model`: Model type of asr task. Default: `conformer_wenetspeech`.
   - `lang`: Model language. Default: `zh`.
+  - `codeswitch`: Code Swith Model. Default: `False`
   - `sample_rate`: Sample rate of the model. Default: `16000`.
   - `config`: Config of asr task. Use pretrained model when it is None. Default: `None`.
   - `ckpt_path`: Model checkpoint. Use pretrained model when it is None. Default: `None`.
@@ -83,14 +86,15 @@ wget -c https://paddlespeech.bj.bcebos.com/PaddleAudio/zh.wav https://paddlespee
 
 Here is a list of pretrained models released by PaddleSpeech that can be used by command and python API:
 
-| Model | Language | Sample Rate
-| :--- | :---: | :---: |
-| conformer_wenetspeech | zh | 16k
-| conformer_online_multicn | zh | 16k
-| conformer_aishell | zh | 16k
-| conformer_online_aishell | zh | 16k
-| transformer_librispeech | en | 16k
-| deepspeech2online_wenetspeech | zh | 16k
-| deepspeech2offline_aishell| zh| 16k
-| deepspeech2online_aishell | zh | 16k
-| deepspeech2offline_librispeech | en | 16k
+| Model | Code Switch | Language | Sample Rate
+| :--- | :---: | :---: | :---: |
+| conformer_wenetspeech | False | zh | 16k
+| conformer_online_multicn | False | zh | 16k
+| conformer_aishell | False | zh | 16k
+| conformer_online_aishell | False | zh | 16k
+| transformer_librispeech | False | en | 16k
+| deepspeech2online_wenetspeech | False | zh | 16k
+| deepspeech2offline_aishell | False | zh| 16k
+| deepspeech2online_aishell | False | zh | 16k
+| deepspeech2offline_librispeech | False | en | 16k
+| conformer_talcs | True | zh_en | 16k

demos/speech_recognition/README_cn.md

@@ -1,4 +1,5 @@
 (简体中文|[English](./README.md))
+ (简体中文|[English](./README.md))
 
 # 语音识别
 ## 介绍
@@ -16,7 +17,7 @@
 
 可以下载此 demo 的示例音频：
 ```bash
-wget -c https://paddlespeech.bj.bcebos.com/PaddleAudio/zh.wav https://paddlespeech.bj.bcebos.com/PaddleAudio/en.wav
+wget -c https://paddlespeech.bj.bcebos.com/PaddleAudio/zh.wav https://paddlespeech.bj.bcebos.com/PaddleAudio/en.wav https://paddlespeech.bj.bcebos.com/PaddleAudio/ch_zh_mix.wav
 ```
 ### 3. 使用方法
 - 命令行 (推荐使用)
@@ -25,6 +26,8 @@ wget -c https://paddlespeech.bj.bcebos.com/PaddleAudio/zh.wav https://paddlespee
   paddlespeech asr --input ./zh.wav -v
   # 英文
   paddlespeech asr --model transformer_librispeech --lang en --input ./en.wav -v
+  #中英混合
+  paddlespeech asr --model conformer_talcs --lang zh_en --codeswitch True --input ./ch_zh_mix.wav -v 
   # 中文 + 标点恢复
   paddlespeech asr --input ./zh.wav -v | paddlespeech text --task punc -v
   ```
@@ -38,6 +41,7 @@ wget -c https://paddlespeech.bj.bcebos.com/PaddleAudio/zh.wav https://paddlespee
   - `input`(必须输入)：用于识别的音频文件。
   - `model`：ASR 任务的模型，默认值：`conformer_wenetspeech`。
   - `lang`：模型语言，默认值：`zh`。
+  - `codeswitch`: 是否使用语言转换，默认值：`False`。
   - `sample_rate`：音频采样率，默认值：`16000`。
   - `config`：ASR 任务的参数文件，若不设置则使用预训练模型中的默认配置，默认值：`None`。
   - `ckpt_path`：模型参数文件，若不设置则下载预训练模型使用，默认值：`None`。
@@ -80,14 +84,15 @@ wget -c https://paddlespeech.bj.bcebos.com/PaddleAudio/zh.wav https://paddlespee
 ### 4.预训练模型
 以下是 PaddleSpeech 提供的可以被命令行和 python API 使用的预训练模型列表：
 
-| 模型 | 语言 | 采样率
-| :--- | :---: | :---: |
-| conformer_wenetspeech | zh | 16k
-| conformer_online_multicn | zh | 16k
-| conformer_aishell | zh | 16k
-| conformer_online_aishell | zh | 16k
-| transformer_librispeech | en | 16k
-| deepspeech2online_wenetspeech | zh | 16k
-| deepspeech2offline_aishell| zh| 16k
-| deepspeech2online_aishell | zh | 16k
-| deepspeech2offline_librispeech | en | 16k
+| 模型 | 语言转换 | 语言 | 采样率
+| :--- | :---: | :---: | :---: |
+| conformer_wenetspeech | False | zh | 16k
+| conformer_online_multicn | False | zh | 16k
+| conformer_aishell | False | zh | 16k
+| conformer_online_aishell | False | zh | 16k
+| transformer_librispeech | False | en | 16k
+| deepspeech2online_wenetspeech | False | zh | 16k
+| deepspeech2offline_aishell | False | zh| 16k
+| deepspeech2online_aishell | False | zh | 16k
+| deepspeech2offline_librispeech | False | en | 16k
+| conformer_talcs | True | zh_en | 16k

demos/speech_recognition/run.sh

@@ -2,6 +2,7 @@
 
 wget -c https://paddlespeech.bj.bcebos.com/PaddleAudio/zh.wav
 wget -c https://paddlespeech.bj.bcebos.com/PaddleAudio/en.wav
+wget -c https://paddlespeech.bj.bcebos.com/PaddleAudio/ch_zh_mix.wav
 
 # asr
 paddlespeech asr --input ./zh.wav
@@ -18,6 +19,11 @@ paddlespeech asr --help
 # english asr
 paddlespeech asr --lang en --model transformer_librispeech --input ./en.wav
 
+
+# code-switch asr
+paddlespeech asr --lang zh_en --codeswitch True --model conformer_talcs --input ./ch_zh_mix.wav
+
+
 # model stats
 paddlespeech stats --task asr
 

paddlespeech/cli/asr/infer.py

@@ -25,6 +25,9 @@
 import numpy as np
 import paddle
 import soundfile
+from paddlespeech.audio.transform.transformation import Transformation
+from paddlespeech.s2t.frontend.featurizer.text_featurizer import TextFeaturizer
+from paddlespeech.s2t.utils.utility import UpdateConfig
 from yacs.config import CfgNode
 
 from ...utils.env import MODEL_HOME
@@ -34,9 +37,6 @@
 from ..utils import CLI_TIMER
 from ..utils import stats_wrapper
 from ..utils import timer_register
-from paddlespeech.audio.transform.transformation import Transformation
-from paddlespeech.s2t.frontend.featurizer.text_featurizer import TextFeaturizer
-from paddlespeech.s2t.utils.utility import UpdateConfig
 
 __all__ = ['ASRExecutor']
 
@@ -62,8 +62,13 @@ def __init__(self):
             '--lang',
             type=str,
             default='zh',
-            help='Choose model language. zh or en, zh:[conformer_wenetspeech-zh-16k], en:[transformer_librispeech-en-16k]'
+            help='Choose model language. [zh, en, zh_en], zh:[conformer_wenetspeech-zh-16k], en:[transformer_librispeech-en-16k], zh_en:[conformer_talcs-codeswitch_zh_en-16k]'
         )
+        self.parser.add_argument(
+            '--codeswitch',
+            type=bool,
+            default=False,
+            help='Choose whether use code-switch. True or False.')
         self.parser.add_argument(
             "--sample_rate",
             type=int,
@@ -127,6 +132,7 @@ def __init__(self):
     def _init_from_path(self,
                         model_type: str='wenetspeech',
                         lang: str='zh',
+                        codeswitch: bool=False,
                         sample_rate: int=16000,
                         cfg_path: Optional[os.PathLike]=None,
                         decode_method: str='attention_rescoring',
@@ -144,7 +150,12 @@ def _init_from_path(self,
 
         if cfg_path is None or ckpt_path is None:
             sample_rate_str = '16k' if sample_rate == 16000 else '8k'
-            tag = model_type + '-' + lang + '-' + sample_rate_str
+            if lang == "zh_en" and codeswitch is True:
+                tag = model_type + '-' + 'codeswitch_' + lang + '-' + sample_rate_str
+            elif lang == "zh_en" or codeswitch is True:
+                raise Exception("codeswitch is true only in zh_en model")
+            else:
+                tag = model_type + '-' + lang + '-' + sample_rate_str
             self.task_resource.set_task_model(tag, version=None)
             self.res_path = self.task_resource.res_dir
 
@@ -423,6 +434,7 @@ def execute(self, argv: List[str]) -> bool:
 
         model = parser_args.model
         lang = parser_args.lang
+        codeswitch = parser_args.codeswitch
         sample_rate = parser_args.sample_rate
         config = parser_args.config
         ckpt_path = parser_args.ckpt_path
@@ -444,6 +456,7 @@ def execute(self, argv: List[str]) -> bool:
                     audio_file=input_,
                     model=model,
                     lang=lang,
+                    codeswitch=codeswitch,
                     sample_rate=sample_rate,
                     config=config,
                     ckpt_path=ckpt_path,
@@ -472,6 +485,7 @@ def __call__(self,
                  audio_file: os.PathLike,
                  model: str='conformer_u2pp_online_wenetspeech',
                  lang: str='zh',
+                 codeswitch: bool=False,
                  sample_rate: int=16000,
                  config: os.PathLike=None,
                  ckpt_path: os.PathLike=None,
@@ -485,8 +499,8 @@ def __call__(self,
         """
         audio_file = os.path.abspath(audio_file)
         paddle.set_device(device)
-        self._init_from_path(model, lang, sample_rate, config, decode_method,
-                             num_decoding_left_chunks, ckpt_path)
+        self._init_from_path(model, lang, codeswitch, sample_rate, config,
+                             decode_method, num_decoding_left_chunks, ckpt_path)
         if not self._check(audio_file, sample_rate, force_yes):
             sys.exit(-1)
         if rtf:

paddlespeech/cli/base_commands.py

@@ -14,6 +14,7 @@
 import argparse
 from typing import List
 
+import numpy
 from prettytable import PrettyTable
 
 from ..resource import CommonTaskResource
@@ -78,7 +79,7 @@ def execute(self, argv: List[str]) -> bool:
 
 
 model_name_format = {
-    'asr': 'Model-Language-Sample Rate',
+    'asr': 'Model-Size-Code Switch-Multilingual-Language-Sample Rate',
     'cls': 'Model-Sample Rate',
     'st': 'Model-Source language-Target language',
     'text': 'Model-Task-Language',
@@ -111,7 +112,21 @@ def show_support_models(self, pretrained_models: dict):
         fields = model_name_format[self.task].split("-")
         table = PrettyTable(fields)
         for key in pretrained_models:
-            table.add_row(key.split("-"))
+            line = key.split("-")
+            if self.task == "asr" and len(line) < len(fields):
+                for i in range(len(line), len(fields)):
+                    line.append("-")
+                if "codeswitch" in key:
+                    line[3], line[1] = line[1].split("_")[0], line[1].split(
+                        "_")[1:]
+                elif "multilingual" in key:
+                    line[4], line[1] = line[1].split("_")[0], line[1].split(
+                        "_")[1:]
+                tmp = numpy.array(line)
+                idx = [0, 5, 3, 4, 1, 2]
+                line = tmp[idx]
+            table.add_row(line)
+
         print(table)
 
     def execute(self, argv: List[str]) -> bool:

paddlespeech/resource/pretrained_models.py

@@ -30,6 +30,7 @@
 ]
 
 # The tags for pretrained_models should be "{model_name}[_{dataset}][-{lang}][-...]".
+# Add code-switch and multilingual tag, "{model_name}[_{dataset}]-[codeswitch/multilingual][_{lang}][-...]".
 # e.g. "conformer_wenetspeech-zh-16k" and "panns_cnn6-32k".
 # Command line and python api use "{model_name}[_{dataset}]" as --model, usage:
 # "paddlespeech asr --model conformer_wenetspeech --lang zh --sr 16000 --input ./input.wav"
@@ -322,6 +323,18 @@
             '099a601759d467cd0a8523ff939819c5'
         },
     },
+    "conformer_talcs-codeswitch_zh_en-16k": {
+        '1.4': {
+            'url':
+            'https://paddlespeech.bj.bcebos.com/s2t/tal_cs/asr1/asr1_conformer_talcs_ckpt_1.4.0.model.tar.gz',
+            'md5':
+            '01962c5d0a70878fe41cacd4f61e14d1',
+            'cfg_path':
+            'model.yaml',
+            'ckpt_path':
+            'exp/conformer/checkpoints/avg_10'
+        },
+    },
 }
 
 asr_static_pretrained_models = {

paddlespeech/server/bin/paddlespeech_server.py

@@ -16,21 +16,22 @@
 import warnings
 from typing import List
 
+import numpy
 import uvicorn
 from fastapi import FastAPI
-from prettytable import PrettyTable
-from starlette.middleware.cors import CORSMiddleware
-
-from ..executor import BaseExecutor
-from ..util import cli_server_register
-from ..util import stats_wrapper
 from paddlespeech.cli.log import logger
 from paddlespeech.resource import CommonTaskResource
 from paddlespeech.server.engine.engine_pool import init_engine_pool
 from paddlespeech.server.engine.engine_warmup import warm_up
 from paddlespeech.server.restful.api import setup_router as setup_http_router
 from paddlespeech.server.utils.config import get_config
 from paddlespeech.server.ws.api import setup_router as setup_ws_router
+from prettytable import PrettyTable
+from starlette.middleware.cors import CORSMiddleware
+
+from ..executor import BaseExecutor
+from ..util import cli_server_register
+from ..util import stats_wrapper
 warnings.filterwarnings("ignore")
 
 __all__ = ['ServerExecutor', 'ServerStatsExecutor']
@@ -134,7 +135,7 @@ def __init__(self):
             required=True)
         self.task_choices = ['asr', 'tts', 'cls', 'text', 'vector']
         self.model_name_format = {
-            'asr': 'Model-Language-Sample Rate',
+            'asr': 'Model-Size-Code Switch-Multilingual-Language-Sample Rate',
             'tts': 'Model-Language',
             'cls': 'Model-Sample Rate',
             'text': 'Model-Task-Language',
@@ -145,7 +146,20 @@ def show_support_models(self, pretrained_models: dict):
         fields = self.model_name_format[self.task].split("-")
         table = PrettyTable(fields)
         for key in pretrained_models:
-            table.add_row(key.split("-"))
+            line = key.split("-")
+            if self.task == "asr" and len(line) < len(fields):
+                for i in range(len(line), len(fields)):
+                    line.append("-")
+                if "codeswitch" in key:
+                    line[3], line[1] = line[1].split("_")[0], line[1].split(
+                        "_")[1:]
+                elif "multilingual" in key:
+                    line[4], line[1] = line[1].split("_")[0], line[1].split(
+                        "_")[1:]
+                tmp = numpy.array(line)
+                idx = [0, 5, 3, 4, 1, 2]
+                line = tmp[idx]
+            table.add_row(line)
         print(table)
 
     def execute(self, argv: List[str]) -> bool:

tests/unit/cli/test_cli.sh

@@ -14,7 +14,7 @@ paddlespeech ssl --task asr --lang en --input ./en.wav
 paddlespeech ssl --task vector --lang en --input ./en.wav
 
 # Speech_recognition
-wget -c https://paddlespeech.bj.bcebos.com/PaddleAudio/zh.wav https://paddlespeech.bj.bcebos.com/PaddleAudio/en.wav
+wget -c https://paddlespeech.bj.bcebos.com/PaddleAudio/zh.wav https://paddlespeech.bj.bcebos.com/PaddleAudio/en.wav https://paddlespeech.bj.bcebos.com/PaddleAudio/ch_zh_mix.wav
 paddlespeech asr --input ./zh.wav
 paddlespeech asr --model conformer_aishell --input ./zh.wav
 paddlespeech asr --model conformer_online_aishell --input ./zh.wav
@@ -26,6 +26,7 @@ paddlespeech asr --model deepspeech2offline_aishell --input ./zh.wav
 paddlespeech asr --model deepspeech2online_wenetspeech --input ./zh.wav
 paddlespeech asr --model deepspeech2online_aishell --input ./zh.wav
 paddlespeech asr --model deepspeech2offline_librispeech --lang en --input ./en.wav
+paddlespeech asr --model conformer_talcs --lang zh_en --codeswitch True --input ./ch_zh_mix.wav
 
 # Support editing num_decoding_left_chunks
 paddlespeech asr --model conformer_online_wenetspeech --num_decoding_left_chunks 3 --input ./zh.wav