如何修复 None 异常迭代请求！问题
How to fix None Exception iterating requests! issue
我刚接触语音识别话题
我正在做一个项目，我可以在其中找到工作区中 Pepper 机器人的一些用例。在使用 Pepper 时，我们发现了它的语音识别能力的一些问题。我发现我们可以尝试将它与外部引擎连接起来，我从 GCP 中选择了 DialogFlow。
也因为我发现了与此服务的一些集成。
我使用了 project
中的代码
import traceback
from naoqi import qi
# [START dialogflow_detect_intent_streaming]
def detect_intent_stream(project_id, session_id, audio_file_path,
language_code,ip):
"""Returns the result of detect intent with streaming audio as input.
Using the same `session_id` between requests allows continuation
of the conversation."""
import dialogflow_v2 as dialogflow
session_client = dialogflow.SessionsClient()
# Note: hard coding audio_encoding and sample_rate_hertz for simplicity.
audio_encoding = dialogflow.enums.AudioEncoding.AUDIO_ENCODING_LINEAR_16
sample_rate_hertz = 44100
session_path = session_client.session_path(project_id, session_id)
print('Session path: {}\n'.format(session_path))
def request_generator(audio_config, audio_file_path):
query_input = dialogflow.types.QueryInput(audio_config=audio_config)
# The first request contains the configuration.
yield dialogflow.types.StreamingDetectIntentRequest(
session=session_path, query_input=query_input)
# Here we are reading small chunks of audio data from a local
# audio file. In practice these chunks should come from
# an audio input device.
try:
with open(audio_file_path, 'rb') as audio_file:
while True:
chunk = audio_file.read(4096)
print(chunk)
if not chunk:
break
except:
traceback.print_exc()
# The later requests contains audio data.
yield dialogflow.types.StreamingDetectIntentRequest(input_audio=chunk)
audio_config = dialogflow.types.InputAudioConfig(audio_encoding=audio_encoding, language_code=language_code, sample_rate_hertz=sample_rate_hertz)
requests = request_generator(audio_config, audio_file_path)
responses = session_client.streaming_detect_intent(requests)
print('=' * 20)
for response in responses:
print('Intermediate transcript: "{}".'.format(response.recognition_result.transcript))
# Note: The result from the last response is the final transcript along
# with the detected content.
query_result = response.query_result
session = qi.Session()
try:
tts = session.service("ALTextToSpeech")
tts.say(query_result.fulfillment_text)
except:
traceback.print_exc()
raise Exception("session.connect failed.")
finally:
session.close()
print('=' * 20)
print('Query text: {}'.format(query_result.query_text))
print('Detected intent: {} (confidence: {})\n'.format(
query_result.intent.display_name,
query_result.intent_detection_confidence))
print('Fulfillment text: {}\n'.format(
query_result.fulfillment_text))
# [END dialogflow_detect_intent_streaming]
已编辑：（添加 pepper_recorder.py 代码）
下面的代码从 Pepper 获取任何声音，并仅将期望峰值发送到对话流 detect_intent_stream
import StringIO
from Queue import Queue
from naoqi import ALModule, ALProxy
import numpy as np
import time
import logging
import uuid
import traceback
from detect_intent_stream import detect_intent_stream
LISTEN_RETRIES = 10
DIALOG_FLOW_GCP_PROJECT_ID = "XXXXXXXXXXXXXXXXXXXX"
class SoundProcessingModule(ALModule):
def __init__( self, name, ip, stop_recognition):
try:
ALModule.__init__( self, name );
except Exception as e:
logging.error(str(e))
pass
print("connected")
self.ip = ip
self.BIND_PYTHON( name, "processRemote")
self.ALAudioDevice = ALProxy("ALAudioDevice", self.ip, 9559)
self.framesCount=0
self.count = LISTEN_RETRIES
self.recordingInProgress = False
self.stopRecognition = stop_recognition
self.uuid = uuid.uuid4()
self.previous_sound_data = None
def startProcessing(self):
"""init sound processing, set microphone and stream rate"""
print("startProcessing")
self.ALAudioDevice.setClientPreferences(self.getName(), 16000, 4, 0)
self.ALAudioDevice.subscribe(self.getName())
while not self.stopRecognition.is_set():
time.sleep(1)
self.ALAudioDevice.unsubscribe(self.getName())
def processRemote(self, nbOfChannels, nbOfSamplesByChannel, timeStamp, inputBuffer):
"""audio stream callback method with simple silence detection"""
self.framesCount = self.framesCount + 1
sound_data_interlaced = np.fromstring(str(inputBuffer), dtype=np.int16)
sound_data = np.reshape(sound_data_interlaced, (nbOfChannels, nbOfSamplesByChannel), 'F')
peak_value = np.max(sound_data)
# detect sound
if peak_value > 10000:
print("Peak:", peak_value)
self.count = LISTEN_RETRIES
if not self.recordingInProgress:
self.startRecording(self.previous_sound_data)
# if there is no sound for a few seconds we end the current recording and start audio processing
if self.count <= 0 and self.recordingInProgress:
self.stopRecording()
# if recording is in progress we save the sound to an in-memory file
if self.recordingInProgress:
self.count -= 1
self.previous_data = sound_data
self.procssingQueue.put(sound_data[0].tostring())
self.outfile.write(sound_data[0].tostring())
def startRecording(self, previous_sound_data):
"""init a in memory file object and save the last raw sound buffer to it."""
self.outfile = StringIO.StringIO()
self.procssingQueue = Queue()
self.recordingInProgress = True
if not previous_sound_data is None:
self.procssingQueue.put(previous_sound_data[0].tostring())
self.outfile.write(previous_sound_data[0].tostring())
print("start recording")
def stopRecording(self):
"""saves the recording to memory"""
print("stopped recording")
self.previous_sound_data = None
self.outfile.seek(0)
try:
detect_intent_stream(DIALOG_FLOW_GCP_PROJECT_ID, self.uuid,
self.outfile, "en-US", self.ip)
except:
traceback.print_exc()
self.recordingInProgress = False
我已连接到机器人，它正在监听，但每次它开始录音时，我都会在控制台中看到类似的内容
('Peak:', 14023)
开始录制
停止录制
会话路径：XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX
====================
然后报错...
追溯（最近调用最后）：
> File
> "C:\Users\marwloda\PycharmProjects\Pepper\scripts\pepper_recorder.py",
> line 83, in stopRecording self.outfile, "en-US", self.ip) File
> "C:\Users\marwloda\PycharmProjects\Pepper\scripts\detect_intent_stream.py",
> line 76, in detect_intent_stream for response in responses: File
> "C:\Users\marwloda\PycharmProjects\Pepper\venv\lib\site-packages\google\api_core\grpc_helpers.py",
> line 81, in next
> six.raise_from(exceptions.from_grpc_error(exc), exc) File "C:\Users\marwloda\PycharmProjects\Pepper\venv\lib\site-packages\six.py",
> line 737, in raise_from
> raise value Unknown: None Exception iterating requests!
如果从机器人记录的 audio_file 是空的。
但是我已经打印了一些语音记录数据并生成了一些原始的不可读字符串
为了证明我与 API 有某种联系 - 当我打开 GCP 控制台 API 和服务时，我看到了这个 view
什么可能导致此错误？
我应该在哪里寻找原因？
您好，您的音频文件或网络连接可能有问题。
您是否尝试过将简单的文本或预先录制的 wav 文件作为输入发送到 dialogflow？
这个脚本在我的胡椒上运行良好：（我的 wav 文件是单声道，44100Hz，32 位）
import os
import time
import sys
import uuid
import google
def printResponse(response):
print('=' * 20)
print('Query text: {}'.format(response.query_result.query_text.encode('utf-8')))
print('Detected intent: {} (confidence: {})'.format(
response.query_result.intent.display_name.encode('utf-8'),
response.query_result.intent_detection_confidence))
print('Fulfillment text: {}'.format(
response.query_result.fulfillment_text.encode('utf-8')))
def detect_intent_audio(project_id, session_id, audio_file_path,
language_code, sample_rate_hertz):
import dialogflow_v2 as dialogflow
session_client = dialogflow.SessionsClient()
# Note: hard coding audio_encoding and sample_rate_hertz for simplicity.
audio_encoding = dialogflow.enums.AudioEncoding.AUDIO_ENCODING_LINEAR_16
session = session_client.session_path(project_id, session_id)
with open(audio_file_path, 'rb') as audio_file:
input_audio = audio_file.read()
audio_config = dialogflow.types.InputAudioConfig(
audio_encoding=audio_encoding, language_code=language_code,
sample_rate_hertz=sample_rate_hertz)
query_input = dialogflow.types.QueryInput(audio_config=audio_config)
response = session_client.detect_intent(
session=session, query_input=query_input,
input_audio=input_audio)
printResponse(response)
def detect_intent_stream(project_id, session_id, audio_file_path,
language_code, sample_rate_hertz):
import dialogflow_v2 as dialogflow
session_client = dialogflow.SessionsClient()
# Note: hard coding audio_encoding and sample_rate_hertz for simplicity.
audio_encoding = dialogflow.enums.AudioEncoding.AUDIO_ENCODING_LINEAR_16
session_path = session_client.session_path(project_id, session_id)
def request_generator(audio_config, audio_file_path):
query_input = dialogflow.types.QueryInput(audio_config=audio_config)
# The first request contains the configuration.
yield dialogflow.types.StreamingDetectIntentRequest(
session=session_path, query_input=query_input)
# Here we are reading small chunks of audio data from a local
# audio file. In practice these chunks should come from
# an audio input device.
with open(audio_file_path, 'rb') as audio_file:
while True:
chunk = audio_file.read(4096)
if not chunk:
break
# The later requests contains audio data.
yield dialogflow.types.StreamingDetectIntentRequest(
input_audio=chunk)
audio_config = dialogflow.types.InputAudioConfig(
audio_encoding=audio_encoding, language_code=language_code,
sample_rate_hertz=sample_rate_hertz)
requests = request_generator(audio_config, audio_file_path)
responses = session_client.streaming_detect_intent(requests)
print('=' * 20)
for response in responses:
print('Intermediate transcript: "{}".'.format(
response.recognition_result.transcript.encode('utf-8')))
# Note: The result from the last response is the final transcript along
# with the detected content.
printResponse(response)
def detect_intent_texts(project_id, session_id, texts, language_code):
import dialogflow_v2 as dialogflow
session_client = dialogflow.SessionsClient()
session = session_client.session_path(project_id, session_id)
for text in texts:
text_input = dialogflow.types.TextInput(
text=text, language_code=language_code)
query_input = dialogflow.types.QueryInput(text=text_input)
response = session_client.detect_intent(
session=session, query_input=query_input)
printResponse(response)
project_id = 'my_project_id'
session_id = str(uuid.uuid4())
language_code = 'de'
os.environ['GOOGLE_APPLICATION_CREDENTIALS'] = os.path.join('/home/me/', 'xyz.json')
wav_path = os.path.join('/home/me/', 'audio.wav')
try:
print ("detect_intent_texts:")
detect_intent_texts(project_id, session_id, ["Hallo"], language_code)
print('=' * 20)
print ("detect_intent_audio:")
detect_intent_audio(project_id, session_id, wav_path, language_code, 44100)
print('=' * 20)
print ("detect_intent_stream:")
detect_intent_stream(project_id, session_id, wav_path, language_code, 44100)
print('=' * 20)
except google.api_core.exceptions.ServiceUnavailable:
print("503 Connect Failed")
很明显，您将 StringIO 传递给 detect_intent_stream 作为 audio_file_path，其中：
with open(audio_file_path, 'rb') as audio_file:
您尝试将 StringIO 作为文件打开
但是：
A StringIO instance is an open file already. The open command, on the
other hand, only takes filenames, to return an open file. A StringIO
instance is not suitable as a filename. link
因此 detect_intent_stream 中的 request_generator 函数需要如下所示：
def request_generator(audio_config, audio_file_path):
query_input = dialogflow.types.QueryInput(audio_config=audio_config)
yield dialogflow.types.StreamingDetectIntentRequest(
session=session_path, query_input=query_input)
while True:
chunk = audio_file_path.read(4096)
if not chunk:
break
yield dialogflow.types.StreamingDetectIntentRequest(
input_audio=chunk)
我刚接触语音识别话题
我正在做一个项目，我可以在其中找到工作区中 Pepper 机器人的一些用例。在使用 Pepper 时，我们发现了它的语音识别能力的一些问题。我发现我们可以尝试将它与外部引擎连接起来，我从 GCP 中选择了 DialogFlow。 也因为我发现了与此服务的一些集成。 我使用了 project
中的代码import traceback
from naoqi import qi
# [START dialogflow_detect_intent_streaming]
def detect_intent_stream(project_id, session_id, audio_file_path,
language_code,ip):
"""Returns the result of detect intent with streaming audio as input.
Using the same `session_id` between requests allows continuation
of the conversation."""
import dialogflow_v2 as dialogflow
session_client = dialogflow.SessionsClient()
# Note: hard coding audio_encoding and sample_rate_hertz for simplicity.
audio_encoding = dialogflow.enums.AudioEncoding.AUDIO_ENCODING_LINEAR_16
sample_rate_hertz = 44100
session_path = session_client.session_path(project_id, session_id)
print('Session path: {}\n'.format(session_path))
def request_generator(audio_config, audio_file_path):
query_input = dialogflow.types.QueryInput(audio_config=audio_config)
# The first request contains the configuration.
yield dialogflow.types.StreamingDetectIntentRequest(
session=session_path, query_input=query_input)
# Here we are reading small chunks of audio data from a local
# audio file. In practice these chunks should come from
# an audio input device.
try:
with open(audio_file_path, 'rb') as audio_file:
while True:
chunk = audio_file.read(4096)
print(chunk)
if not chunk:
break
except:
traceback.print_exc()
# The later requests contains audio data.
yield dialogflow.types.StreamingDetectIntentRequest(input_audio=chunk)
audio_config = dialogflow.types.InputAudioConfig(audio_encoding=audio_encoding, language_code=language_code, sample_rate_hertz=sample_rate_hertz)
requests = request_generator(audio_config, audio_file_path)
responses = session_client.streaming_detect_intent(requests)
print('=' * 20)
for response in responses:
print('Intermediate transcript: "{}".'.format(response.recognition_result.transcript))
# Note: The result from the last response is the final transcript along
# with the detected content.
query_result = response.query_result
session = qi.Session()
try:
tts = session.service("ALTextToSpeech")
tts.say(query_result.fulfillment_text)
except:
traceback.print_exc()
raise Exception("session.connect failed.")
finally:
session.close()
print('=' * 20)
print('Query text: {}'.format(query_result.query_text))
print('Detected intent: {} (confidence: {})\n'.format(
query_result.intent.display_name,
query_result.intent_detection_confidence))
print('Fulfillment text: {}\n'.format(
query_result.fulfillment_text))
# [END dialogflow_detect_intent_streaming]
已编辑：（添加 pepper_recorder.py 代码） 下面的代码从 Pepper 获取任何声音，并仅将期望峰值发送到对话流 detect_intent_stream
import StringIO
from Queue import Queue
from naoqi import ALModule, ALProxy
import numpy as np
import time
import logging
import uuid
import traceback
from detect_intent_stream import detect_intent_stream
LISTEN_RETRIES = 10
DIALOG_FLOW_GCP_PROJECT_ID = "XXXXXXXXXXXXXXXXXXXX"
class SoundProcessingModule(ALModule):
def __init__( self, name, ip, stop_recognition):
try:
ALModule.__init__( self, name );
except Exception as e:
logging.error(str(e))
pass
print("connected")
self.ip = ip
self.BIND_PYTHON( name, "processRemote")
self.ALAudioDevice = ALProxy("ALAudioDevice", self.ip, 9559)
self.framesCount=0
self.count = LISTEN_RETRIES
self.recordingInProgress = False
self.stopRecognition = stop_recognition
self.uuid = uuid.uuid4()
self.previous_sound_data = None
def startProcessing(self):
"""init sound processing, set microphone and stream rate"""
print("startProcessing")
self.ALAudioDevice.setClientPreferences(self.getName(), 16000, 4, 0)
self.ALAudioDevice.subscribe(self.getName())
while not self.stopRecognition.is_set():
time.sleep(1)
self.ALAudioDevice.unsubscribe(self.getName())
def processRemote(self, nbOfChannels, nbOfSamplesByChannel, timeStamp, inputBuffer):
"""audio stream callback method with simple silence detection"""
self.framesCount = self.framesCount + 1
sound_data_interlaced = np.fromstring(str(inputBuffer), dtype=np.int16)
sound_data = np.reshape(sound_data_interlaced, (nbOfChannels, nbOfSamplesByChannel), 'F')
peak_value = np.max(sound_data)
# detect sound
if peak_value > 10000:
print("Peak:", peak_value)
self.count = LISTEN_RETRIES
if not self.recordingInProgress:
self.startRecording(self.previous_sound_data)
# if there is no sound for a few seconds we end the current recording and start audio processing
if self.count <= 0 and self.recordingInProgress:
self.stopRecording()
# if recording is in progress we save the sound to an in-memory file
if self.recordingInProgress:
self.count -= 1
self.previous_data = sound_data
self.procssingQueue.put(sound_data[0].tostring())
self.outfile.write(sound_data[0].tostring())
def startRecording(self, previous_sound_data):
"""init a in memory file object and save the last raw sound buffer to it."""
self.outfile = StringIO.StringIO()
self.procssingQueue = Queue()
self.recordingInProgress = True
if not previous_sound_data is None:
self.procssingQueue.put(previous_sound_data[0].tostring())
self.outfile.write(previous_sound_data[0].tostring())
print("start recording")
def stopRecording(self):
"""saves the recording to memory"""
print("stopped recording")
self.previous_sound_data = None
self.outfile.seek(0)
try:
detect_intent_stream(DIALOG_FLOW_GCP_PROJECT_ID, self.uuid,
self.outfile, "en-US", self.ip)
except:
traceback.print_exc()
self.recordingInProgress = False
我已连接到机器人，它正在监听，但每次它开始录音时，我都会在控制台中看到类似的内容
('Peak:', 14023)
开始录制
停止录制
会话路径：XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX
====================
然后报错...
追溯（最近调用最后）：
> File
> "C:\Users\marwloda\PycharmProjects\Pepper\scripts\pepper_recorder.py",
> line 83, in stopRecording self.outfile, "en-US", self.ip) File
> "C:\Users\marwloda\PycharmProjects\Pepper\scripts\detect_intent_stream.py",
> line 76, in detect_intent_stream for response in responses: File
> "C:\Users\marwloda\PycharmProjects\Pepper\venv\lib\site-packages\google\api_core\grpc_helpers.py",
> line 81, in next
> six.raise_from(exceptions.from_grpc_error(exc), exc) File "C:\Users\marwloda\PycharmProjects\Pepper\venv\lib\site-packages\six.py",
> line 737, in raise_from
> raise value Unknown: None Exception iterating requests!
如果从机器人记录的 audio_file 是空的。 但是我已经打印了一些语音记录数据并生成了一些原始的不可读字符串
为了证明我与 API 有某种联系 - 当我打开 GCP 控制台 API 和服务时，我看到了这个 view
什么可能导致此错误？ 我应该在哪里寻找原因？
您好，您的音频文件或网络连接可能有问题。 您是否尝试过将简单的文本或预先录制的 wav 文件作为输入发送到 dialogflow？
这个脚本在我的胡椒上运行良好：（我的 wav 文件是单声道，44100Hz，32 位）
import os
import time
import sys
import uuid
import google
def printResponse(response):
print('=' * 20)
print('Query text: {}'.format(response.query_result.query_text.encode('utf-8')))
print('Detected intent: {} (confidence: {})'.format(
response.query_result.intent.display_name.encode('utf-8'),
response.query_result.intent_detection_confidence))
print('Fulfillment text: {}'.format(
response.query_result.fulfillment_text.encode('utf-8')))
def detect_intent_audio(project_id, session_id, audio_file_path,
language_code, sample_rate_hertz):
import dialogflow_v2 as dialogflow
session_client = dialogflow.SessionsClient()
# Note: hard coding audio_encoding and sample_rate_hertz for simplicity.
audio_encoding = dialogflow.enums.AudioEncoding.AUDIO_ENCODING_LINEAR_16
session = session_client.session_path(project_id, session_id)
with open(audio_file_path, 'rb') as audio_file:
input_audio = audio_file.read()
audio_config = dialogflow.types.InputAudioConfig(
audio_encoding=audio_encoding, language_code=language_code,
sample_rate_hertz=sample_rate_hertz)
query_input = dialogflow.types.QueryInput(audio_config=audio_config)
response = session_client.detect_intent(
session=session, query_input=query_input,
input_audio=input_audio)
printResponse(response)
def detect_intent_stream(project_id, session_id, audio_file_path,
language_code, sample_rate_hertz):
import dialogflow_v2 as dialogflow
session_client = dialogflow.SessionsClient()
# Note: hard coding audio_encoding and sample_rate_hertz for simplicity.
audio_encoding = dialogflow.enums.AudioEncoding.AUDIO_ENCODING_LINEAR_16
session_path = session_client.session_path(project_id, session_id)
def request_generator(audio_config, audio_file_path):
query_input = dialogflow.types.QueryInput(audio_config=audio_config)
# The first request contains the configuration.
yield dialogflow.types.StreamingDetectIntentRequest(
session=session_path, query_input=query_input)
# Here we are reading small chunks of audio data from a local
# audio file. In practice these chunks should come from
# an audio input device.
with open(audio_file_path, 'rb') as audio_file:
while True:
chunk = audio_file.read(4096)
if not chunk:
break
# The later requests contains audio data.
yield dialogflow.types.StreamingDetectIntentRequest(
input_audio=chunk)
audio_config = dialogflow.types.InputAudioConfig(
audio_encoding=audio_encoding, language_code=language_code,
sample_rate_hertz=sample_rate_hertz)
requests = request_generator(audio_config, audio_file_path)
responses = session_client.streaming_detect_intent(requests)
print('=' * 20)
for response in responses:
print('Intermediate transcript: "{}".'.format(
response.recognition_result.transcript.encode('utf-8')))
# Note: The result from the last response is the final transcript along
# with the detected content.
printResponse(response)
def detect_intent_texts(project_id, session_id, texts, language_code):
import dialogflow_v2 as dialogflow
session_client = dialogflow.SessionsClient()
session = session_client.session_path(project_id, session_id)
for text in texts:
text_input = dialogflow.types.TextInput(
text=text, language_code=language_code)
query_input = dialogflow.types.QueryInput(text=text_input)
response = session_client.detect_intent(
session=session, query_input=query_input)
printResponse(response)
project_id = 'my_project_id'
session_id = str(uuid.uuid4())
language_code = 'de'
os.environ['GOOGLE_APPLICATION_CREDENTIALS'] = os.path.join('/home/me/', 'xyz.json')
wav_path = os.path.join('/home/me/', 'audio.wav')
try:
print ("detect_intent_texts:")
detect_intent_texts(project_id, session_id, ["Hallo"], language_code)
print('=' * 20)
print ("detect_intent_audio:")
detect_intent_audio(project_id, session_id, wav_path, language_code, 44100)
print('=' * 20)
print ("detect_intent_stream:")
detect_intent_stream(project_id, session_id, wav_path, language_code, 44100)
print('=' * 20)
except google.api_core.exceptions.ServiceUnavailable:
print("503 Connect Failed")
很明显，您将 StringIO 传递给 detect_intent_stream 作为 audio_file_path，其中：
with open(audio_file_path, 'rb') as audio_file:
您尝试将 StringIO 作为文件打开
但是：
A StringIO instance is an open file already. The open command, on the other hand, only takes filenames, to return an open file. A StringIO instance is not suitable as a filename. link
因此 detect_intent_stream 中的 request_generator 函数需要如下所示：
def request_generator(audio_config, audio_file_path):
query_input = dialogflow.types.QueryInput(audio_config=audio_config)
yield dialogflow.types.StreamingDetectIntentRequest(
session=session_path, query_input=query_input)
while True:
chunk = audio_file_path.read(4096)
if not chunk:
break
yield dialogflow.types.StreamingDetectIntentRequest(
input_audio=chunk)