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社区首页 >问答首页 >如何将音频文件从S3桶直接传送到Google语音到文本

如何将音频文件从S3桶直接传送到Google语音到文本
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Stack Overflow用户
提问于 2020-12-23 10:38:37
回答 1查看 526关注 0票数 3

我们正在使用Google的语音到文本API开发一个语音应用程序。现在,我们的数据(音频文件)存储在AWS上的S3桶中。有办法直接将S3 URI传递给Google的语音到文本API吗?

从他们的文档来看,在Google的语音到文本API中,这在目前看来是不可能的。

对于他们的愿景和NLP API来说,情况并非如此。

  1. 你知道为什么对语音API有这样的限制吗?
  2. 这里有什么好工作要做?
EN

回答 1

Stack Overflow用户

发布于 2021-01-07 08:23:17

目前,谷歌的只允许音频文件从您的本地来源或谷歌的云存储。对这方面的文件没有给予合理的解释。

传递由URI引用的音频更典型地,您将在语音请求的音频字段中传递一个uri参数,指向位于Google上的音频文件(二进制格式,而不是base64)

我建议你把你的文件移到。如果您不愿意,有一个很好的解决办法:将与流API结合使用。你不需要在任何地方储存任何东西。您的语音应用程序提供来自任何麦克风的输入。如果你不知道如何处理来自麦克风的输入,那就别担心。

谷歌提供了一个样本代码来完成这一切:

代码语言:javascript
代码运行次数:0
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# [START speech_transcribe_streaming_mic]
from __future__ import division

import re
import sys

from google.cloud import speech

import pyaudio
from six.moves import queue

# Audio recording parameters
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

        # Create a thread-safe buffer of audio data
        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,
            # Run the audio stream asynchronously to fill the buffer object.
            # This is necessary so that the input device's buffer doesn't
            # overflow while the calling thread makes network requests, etc.
            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
        # Signal the generator to terminate so that the client's
        # streaming_recognize method will not block the process termination.
        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:
            # Use a blocking get() to ensure there's at least one chunk of
            # data, and stop iteration if the chunk is None, indicating the
            # end of the audio stream.
            chunk = self._buff.get()
            if chunk is None:
                return
            data = [chunk]

            # Now consume whatever other data's still buffered.
            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 the documentation.  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

        # The `results` list is consecutive. For streaming, we only care about
        # the first result being considered, since once it's `is_final`, it
        # moves on to considering the next utterance.
        result = response.results[0]
        if not result.alternatives:
            continue

        # Display the transcription of the top alternative.
        transcript = result.alternatives[0].transcript

        # Display interim results, but with a carriage return at the end of the
        # line, so subsequent lines will overwrite them.
        #
        # If the previous result was longer than this one, we need to print
        # some extra spaces to overwrite the previous result
        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)

            # Exit recognition if any of the transcribed phrases could be
            # one of our keywords.
            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)

        # Now, put the transcription responses to use.
        listen_print_loop(responses)


if __name__ == "__main__":
    main()
# [END speech_transcribe_streaming_mic]

依赖关系是google-cloud-speechpyaudio

对于AWS S3,您可以在从Google获得记录稿之前/之后将您的音频文件存储在那里。流也是超快的。

别忘了附上你的证件。您需要首先通过提供GOOGLE_APPLICATION_CREDENTIALS获得授权

票数 1
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页面原文内容由Stack Overflow提供。腾讯云小微IT领域专用引擎提供翻译支持
原文链接:

https://stackoverflow.com/questions/65422902

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