GCP speech to text のエラーについて

前提・実現したいこと

GCP speech to textでストリーミング文字起こしをしたい。
ここに質問の内容を詳しく書いてください。
Googleが掲載しているサンプルコードで試したところ、始めは出来たのですが2回以降エラーがでるようになりました。いろいろと調べているのですが、解決策が分かりません。
宜しくお願い致します。

発生している問題・エラーメッセージ

AttributeError                            Traceback (most recent call last)
<ipython-input-5-6e34b0a43110> in <module>
    163 
    164 if __name__ == "__main__":
--> 165     main()

<ipython-input-5-6e34b0a43110> in main()
    139     language_code = "en-US"  # a BCP-47 language tag
    140 
--> 141     client = speech.SpeechClient()
    142     config = speech.RecognitionConfig(
    143         encoding=speech.RecognitionConfig.AudioEncoding.LINEAR16,

AttributeError: module 'google.cloud.speech' has no attribute 'SpeechClient'

該当のソースコード

from future import division

import re
import sys

from google.cloud import speech

import pyaudio
from six.moves import queue

RATE = 16000
CHUNK = int(RATE / 10) # 100ms

class MicrophoneStream(object):
"""Opens a recording stream as a generator yielding the audio chunks."""

def __init__(self, rate, chunk):
    self._rate = rate
    self._chunk = chunk

    
    self._buff = queue.Queue()
    self.closed = True

def __enter__(self):
    self._audio_interface = pyaudio.PyAudio()
    self._audio_stream = self._audio_interface.open(
        format=pyaudio.paInt16,
        channels=1,
        rate=self._rate,
        input=True,
        frames_per_buffer=self._chunk,
        stream_callback=self._fill_buffer,
    )

    self.closed = False

    return self

def __exit__(self, type, value, traceback):
    self._audio_stream.stop_stream()
    self._audio_stream.close()
    self.closed = True
    self._buff.put(None)
    self._audio_interface.terminate()

def _fill_buffer(self, in_data, frame_count, time_info, status_flags):
    """Continuously collect data from the audio stream, into the buffer."""
    self._buff.put(in_data)
    return None, pyaudio.paContinue

def generator(self):
    while not self.closed:
        chunk = self._buff.get()
        if chunk is None:
            return
        data = [chunk]
        while True:
            try:
                chunk = self._buff.get(block=False)
                if chunk is None:
                    return
                data.append(chunk)
            except queue.Empty:
                break

        yield b"".join(data)

def listen_print_loop(responses):
"""Iterates through server responses and prints them.

The responses passed is a generator that will block until a response
is provided by the server.

Each response may contain multiple results, and each result may contain
multiple alternatives; for details, see https://goo.gl/tjCPAU.  Here we
print only the transcription for the top alternative of the top result.

In this case, responses are provided for interim results as well. If the
response is an interim one, print a line feed at the end of it, to allow
the next result to overwrite it, until the response is a final one. For the
final one, print a newline to preserve the finalized transcription.
"""
num_chars_printed = 0
for response in responses:
    if not response.results:
        continue
    result = response.results[0]
    if not result.alternatives:
        continue

    transcript = result.alternatives[0].transcript

    overwrite_chars = " " * (num_chars_printed - len(transcript))

    if not result.is_final:
        sys.stdout.write(transcript + overwrite_chars + "\r")
        sys.stdout.flush()

        num_chars_printed = len(transcript)

    else:
        print(transcript + overwrite_chars)

        if re.search(r"\b(exit|quit)\b", transcript, re.I):
            print("Exiting..")
            break

        num_chars_printed = 0

def main():
language_code = "en-US" # a BCP-47 language tag

client = speech.SpeechClient()
config = speech.RecognitionConfig(
    encoding=speech.RecognitionConfig.AudioEncoding.LINEAR16,
    sample_rate_hertz=RATE,
    language_code=language_code,
)

streaming_config = speech.StreamingRecognitionConfig(
    config=config, interim_results=True
)

with MicrophoneStream(RATE, CHUNK) as stream:
    audio_generator = stream.generator()
    requests = (
        speech.StreamingRecognizeRequest(audio_content=content)
        for content in audio_generator
    )

    responses = client.streaming_recognize(streaming_config, requests)

    listen_print_loop(responses)

if name == "main":
main()