[ASR] add asr code-switch cli and demo, test='asr' (#2816)

* add asr code-switch cli and demo. * fix some model named problem.
1 year ago · 88fe26f17c
parent 2c4c141de5
commit 88fe26f17c
10 changed files with 118 additions and 42 deletions
--- a/README.md
+++ b/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
--- a/README_cn.md
+++ b/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！
--- a/demos/speech_recognition/README.md
+++ b/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
--- a/demos/speech_recognition/README_cn.md
+++ b/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
--- a/demos/speech_recognition/run.sh
+++ b/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

--- a/paddlespeech/cli/asr/infer.py
+++ b/paddlespeech/cli/asr/infer.py
@ -25,6 +25,9 @@ import librosa
 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 ..log import logger
 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 @@ class ASRExecutor(BaseExecutor):
            '--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 @@ class ASRExecutor(BaseExecutor):
    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 @@ class ASRExecutor(BaseExecutor):

        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 @@ class ASRExecutor(BaseExecutor):

        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 @@ class ASRExecutor(BaseExecutor):
                    audio_file=input_,
                    model=model,
                    lang=lang,
+                    codeswitch=codeswitch,
                    sample_rate=sample_rate,
                    config=config,
                    ckpt_path=ckpt_path,
@ -472,6 +485,7 @@ class ASRExecutor(BaseExecutor):
                 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 @@ class ASRExecutor(BaseExecutor):
        """
        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:
--- a/paddlespeech/cli/base_commands.py
+++ b/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 @@ class VersionCommand:


 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 @@ class StatsCommand:
        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:
--- a/paddlespeech/resource/pretrained_models.py
+++ b/paddlespeech/resource/pretrained_models.py
@ -30,6 +30,7 @@ __all__ = [
 ]

 # 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 @@ asr_dynamic_pretrained_models = {
            '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 = {
--- a/paddlespeech/server/bin/paddlespeech_server.py
+++ b/paddlespeech/server/bin/paddlespeech_server.py
@ -16,14 +16,9 @@ import sys
 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
@ -31,6 +26,12 @@ 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 @@ class ServerStatsExecutor():
            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 @@ class ServerStatsExecutor():
        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:
--- a/tests/unit/cli/test_cli.sh
+++ b/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