Python 谷歌语音API转录响应被重复多次

我正在使用google cloud speech（0.35.0）的最新python库，我得到的结果如下，第一个转录结果中的单词在第二个转录结果中重复，以此类推，直到最后。以前的版本（0.34.0）并非如此

参考源代码

源代码：

config = speech.types.RecognitionConfig(
            encoding=enums.RecognitionConfig.AudioEncoding.FLAC,
            sample_rate_hertz=48000,
            language_code='en-US',
            alternative_language_codes={'en-IN'},
            # max_alternatives=10,
            profanity_filter=True,
            enable_word_time_offsets=True,
            enable_word_confidence=True,
            enable_automatic_punctuation=True,
            enable_speaker_diarization=True,
            diarization_speaker_count=5,
            #model="video",
            use_enhanced=True)

results {
    alternatives {
        transcript: "start"
        confidence: 0.632519185543
        words {
            start_time {}
            end_time {
                seconds: 5
                nanos: 900000000
            }
            word: "start"
            confidence: 0.655210196972
            speaker_tag: 1
        }
    }
}

.....
.....
.....

results {
    alternatives {
        transcript: "end"
        confidence: 0.632519185543
        words {
            start_time {}
            end_time {
                seconds: 5
                nanos: 900000000
            }
            word: "start"
            confidence: 0.655210196972
            speaker_tag: 1
        }
        words {
            start_time {
                seconds: 129
                nanos: 300000000
            }
            end_time {
                seconds: 130
                nanos: 400000000
            }
            word: "end"
            confidence: 0.624447464943
            speaker_tag: 1
        }

    }
}

结果：

config = speech.types.RecognitionConfig(
            encoding=enums.RecognitionConfig.AudioEncoding.FLAC,
            sample_rate_hertz=48000,
            language_code='en-US',
            alternative_language_codes={'en-IN'},
            # max_alternatives=10,
            profanity_filter=True,
            enable_word_time_offsets=True,
            enable_word_confidence=True,
            enable_automatic_punctuation=True,
            enable_speaker_diarization=True,
            diarization_speaker_count=5,
            #model="video",
            use_enhanced=True)

results {
    alternatives {
        transcript: "start"
        confidence: 0.632519185543
        words {
            start_time {}
            end_time {
                seconds: 5
                nanos: 900000000
            }
            word: "start"
            confidence: 0.655210196972
            speaker_tag: 1
        }
    }
}

.....
.....
.....

results {
    alternatives {
        transcript: "end"
        confidence: 0.632519185543
        words {
            start_time {}
            end_time {
                seconds: 5
                nanos: 900000000
            }
            word: "start"
            confidence: 0.655210196972
            speaker_tag: 1
        }
        words {
            start_time {
                seconds: 129
                nanos: 300000000
            }
            end_time {
                seconds: 130
                nanos: 400000000
            }
            word: "end"
            confidence: 0.624447464943
            speaker_tag: 1
        }

    }
}

问题：

config = speech.types.RecognitionConfig(
            encoding=enums.RecognitionConfig.AudioEncoding.FLAC,
            sample_rate_hertz=48000,
            language_code='en-US',
            alternative_language_codes={'en-IN'},
            # max_alternatives=10,
            profanity_filter=True,
            enable_word_time_offsets=True,
            enable_word_confidence=True,
            enable_automatic_punctuation=True,
            enable_speaker_diarization=True,
            diarization_speaker_count=5,
            #model="video",
            use_enhanced=True)

results {
    alternatives {
        transcript: "start"
        confidence: 0.632519185543
        words {
            start_time {}
            end_time {
                seconds: 5
                nanos: 900000000
            }
            word: "start"
            confidence: 0.655210196972
            speaker_tag: 1
        }
    }
}

.....
.....
.....

results {
    alternatives {
        transcript: "end"
        confidence: 0.632519185543
        words {
            start_time {}
            end_time {
                seconds: 5
                nanos: 900000000
            }
            word: "start"
            confidence: 0.655210196972
            speaker_tag: 1
        }
        words {
            start_time {
                seconds: 129
                nanos: 300000000
            }
            end_time {
                seconds: 130
                nanos: 400000000
            }
            word: "end"
            confidence: 0.624447464943
            speaker_tag: 1
        }

    }
}

为什么我在回复中得到多个结果

在所有结果集中重复单词的原因是什么？以前，每个结果集只包含在该时间范围内说出的单词

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谷歌似乎在他们的文档中记录了类似的内容

注意：如果这是真的，我们将发送从 每个连续响应中的顶级备选方案的音频。这 这样做是为了在我们的模型学习时改进我们的扬声器标签 随着时间的推移，确定对话中的发言人

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您能否包含打印响应结果的代码部分？