[to #42322933] add httpurl support for ASR

Link: https://code.alibaba-inc.com/Ali-MaaS/MaaS-lib/codereview/10043608

modelscope/pipelines/audio/asr_inference_pipeline.py

@@ -1,4 +1,3 @@
-import os
 from typing import Any, Dict, List, Sequence, Tuple, Union
 
 import yaml
@@ -9,6 +8,8 @@ from modelscope.outputs import OutputKeys
 from modelscope.pipelines.base import Pipeline
 from modelscope.pipelines.builder import PIPELINES
 from modelscope.preprocessors import WavToScp
+from modelscope.utils.audio.audio_utils import (extract_pcm_from_wav,
+                                                load_bytes_from_url)
 from modelscope.utils.constant import Frameworks, Tasks
 from modelscope.utils.logger import get_logger
 
@@ -41,12 +42,20 @@ class AutomaticSpeechRecognitionPipeline(Pipeline):
 
         self.recog_type = recog_type
         self.audio_format = audio_format
-        self.audio_in = audio_in
         self.audio_fs = audio_fs
 
+        if isinstance(audio_in, str):
+            # load pcm data from url if audio_in is url str
+            self.audio_in = load_bytes_from_url(audio_in)
+        elif isinstance(audio_in, bytes):
+            # load pcm data from wav data if audio_in is wave format
+            self.audio_in = extract_pcm_from_wav(audio_in)
+        else:
+            self.audio_in = audio_in
+
         if recog_type is None or audio_format is None:
             self.recog_type, self.audio_format, self.audio_in = asr_utils.type_checking(
-                audio_in=audio_in,
+                audio_in=self.audio_in,
                 recog_type=recog_type,
                 audio_format=audio_format)
 

modelscope/utils/audio/audio_utils.py

@@ -1,4 +1,10 @@
 # Copyright (c) Alibaba, Inc. and its affiliates.
+import struct
+from typing import Union
+from urllib.parse import urlparse
+
+from modelscope.fileio.file import HTTPStorage
+
 SEGMENT_LENGTH_TRAIN = 16000
 
 
@@ -29,3 +35,41 @@ def audio_norm(x):
     scalarx = 10**(-25 / 20) / rmsx
     x = x * scalarx
     return x
+
+
+def extract_pcm_from_wav(wav: bytes) -> bytes:
+    data = wav
+    if len(data) > 44:
+        frame_len = 44
+        file_len = len(data)
+        header_fields = {}
+        header_fields['ChunkID'] = str(data[0:4], 'UTF-8')
+        header_fields['Format'] = str(data[8:12], 'UTF-8')
+        header_fields['Subchunk1ID'] = str(data[12:16], 'UTF-8')
+        if header_fields['ChunkID'] == 'RIFF' and header_fields[
+                'Format'] == 'WAVE' and header_fields['Subchunk1ID'] == 'fmt ':
+            header_fields['SubChunk1Size'] = struct.unpack('<I',
+                                                           data[16:20])[0]
+
+            if header_fields['SubChunk1Size'] == 16:
+                frame_len = 44
+            elif header_fields['SubChunk1Size'] == 18:
+                frame_len = 46
+            else:
+                return data
+
+            data = wav[frame_len:file_len]
+
+    return data
+
+
+def load_bytes_from_url(url: str) -> Union[bytes, str]:
+    result = urlparse(url)
+    if result.scheme is not None and len(result.scheme) > 0:
+        storage = HTTPStorage()
+        data = storage.read(url)
+        data = extract_pcm_from_wav(data)
+    else:
+        data = url
+
+    return data

tests/pipelines/test_automatic_speech_recognition.py

@@ -16,16 +16,11 @@ from modelscope.utils.test_utils import download_and_untar, test_level
 logger = get_logger()
 
 WAV_FILE = 'data/test/audios/asr_example.wav'
+URL_FILE = 'https://isv-data.oss-cn-hangzhou.aliyuncs.com/ics/MaaS/ASR/test_audio/asr_example.wav'
 
 LITTLE_TESTSETS_FILE = 'data_aishell.tar.gz'
 LITTLE_TESTSETS_URL = 'https://isv-data.oss-cn-hangzhou.aliyuncs.com/ics/MaaS/ASR/datasets/data_aishell.tar.gz'
 
-AISHELL1_TESTSETS_FILE = 'aishell1.tar.gz'
-AISHELL1_TESTSETS_URL = 'https://isv-data.oss-cn-hangzhou.aliyuncs.com/ics/MaaS/ASR/datasets/aishell1.tar.gz'
-
-TFRECORD_TESTSETS_FILE = 'tfrecord.tar.gz'
-TFRECORD_TESTSETS_URL = 'https://isv-data.oss-cn-hangzhou.aliyuncs.com/ics/MaaS/ASR/datasets/tfrecord.tar.gz'
-
 
 class AutomaticSpeechRecognitionTest(unittest.TestCase):
     action_info = {
@@ -45,6 +40,10 @@ class AutomaticSpeechRecognitionTest(unittest.TestCase):
             'checking_item': OutputKeys.TEXT,
             'example': 'wav_example'
         },
+        'test_run_with_url_tf': {
+            'checking_item': OutputKeys.TEXT,
+            'example': 'wav_example'
+        },
         'test_run_with_wav_dataset_pytorch': {
             'checking_item': OutputKeys.TEXT,
             'example': 'dataset_example'
@@ -132,8 +131,8 @@ class AutomaticSpeechRecognitionTest(unittest.TestCase):
 
     @unittest.skipUnless(test_level() >= 0, 'skip test in current test level')
     def test_run_with_wav_pytorch(self):
-        '''run with single waveform file
-        '''
+        """run with single waveform file
+        """
 
         logger.info('Run ASR test with waveform file (pytorch)...')
 
@@ -145,8 +144,8 @@ class AutomaticSpeechRecognitionTest(unittest.TestCase):
 
     @unittest.skipUnless(test_level() >= 0, 'skip test in current test level')
     def test_run_with_pcm_pytorch(self):
-        '''run with wav data
-        '''
+        """run with wav data
+        """
 
         logger.info('Run ASR test with wav data (pytorch)...')
 
@@ -158,8 +157,8 @@ class AutomaticSpeechRecognitionTest(unittest.TestCase):
 
     @unittest.skipUnless(test_level() >= 0, 'skip test in current test level')
     def test_run_with_wav_tf(self):
-        '''run with single waveform file
-        '''
+        """run with single waveform file
+        """
 
         logger.info('Run ASR test with waveform file (tensorflow)...')
 
@@ -171,8 +170,8 @@ class AutomaticSpeechRecognitionTest(unittest.TestCase):
 
     @unittest.skipUnless(test_level() >= 0, 'skip test in current test level')
     def test_run_with_pcm_tf(self):
-        '''run with wav data
-        '''
+        """run with wav data
+        """
 
         logger.info('Run ASR test with wav data (tensorflow)...')
 
@@ -182,9 +181,20 @@ class AutomaticSpeechRecognitionTest(unittest.TestCase):
             model_id=self.am_tf_model_id, audio_in=audio, sr=sr)
         self.check_result('test_run_with_pcm_tf', rec_result)
 
+    @unittest.skipUnless(test_level() >= 0, 'skip test in current test level')
+    def test_run_with_url_tf(self):
+        """run with single url file
+        """
+
+        logger.info('Run ASR test with url file (tensorflow)...')
+
+        rec_result = self.run_pipeline(
+            model_id=self.am_tf_model_id, audio_in=URL_FILE)
+        self.check_result('test_run_with_url_tf', rec_result)
+
     @unittest.skipUnless(test_level() >= 1, 'skip test in current test level')
     def test_run_with_wav_dataset_pytorch(self):
-        '''run with datasets, and audio format is waveform
+        """run with datasets, and audio format is waveform
            datasets directory:
              <dataset_path>
                wav
@@ -199,7 +209,7 @@ class AutomaticSpeechRecognitionTest(unittest.TestCase):
                    ...
                transcript
                  data.text  # hypothesis text
-        '''
+        """
 
         logger.info('Run ASR test with waveform dataset (pytorch)...')
         logger.info('Downloading waveform testsets file ...')
@@ -215,7 +225,7 @@ class AutomaticSpeechRecognitionTest(unittest.TestCase):
 
     @unittest.skipUnless(test_level() >= 1, 'skip test in current test level')
     def test_run_with_wav_dataset_tf(self):
-        '''run with datasets, and audio format is waveform
+        """run with datasets, and audio format is waveform
            datasets directory:
              <dataset_path>
                wav
@@ -230,7 +240,7 @@ class AutomaticSpeechRecognitionTest(unittest.TestCase):
                    ...
                transcript
                  data.text  # hypothesis text
-        '''
+        """
 
         logger.info('Run ASR test with waveform dataset (tensorflow)...')
         logger.info('Downloading waveform testsets file ...')