Python for/while循环

Question

今天，我正在做一个关于来电被转录并被保存到文本文件中的项目，但我对python和python循环也有点陌生。我想在SQL server列上循环，让每行循环通过我使用的蔚蓝的语音到文本服务(所有的电话机OID)。我在这个问题上已经被困了几天了，所以我想我可能会在这里找到一些帮助。

import azure.cognitiveservices.speech as speechsdk
import time
from os import path
from pydub import AudioSegment
import requests
import hashlib
import sys
import os.path
import pyodbc

databaseName = '*'
username = '*'
password = '*'
server = '*'
driver = '*'

try:
    CONNECTION_STRING = 'DRIVER='+driver+';SERVER='+server+';DATABASE='+databaseName+';UID='+username+';PWD='+ password

    conn = pyodbc.connect(CONNECTION_STRING)

    cursor = conn.cursor()
    storedproc = "* = *'"
    cursor.execute(storedproc)
    row = cursor.fetchone()
    while row:
        array = [(int(row[1]))]
        row = cursor.fetchone()

        i = 0
        while i<len(array):
            OID = (array[i])
            i = i + 1
            print(OID)


        string = f"{OID}*"
        encoded = string.encode()
        result = hashlib.sha256(encoded)
        resultHash = (result.hexdigest())

        Telefoongesprek = requests.get(f"*{OID}", headers={f"api-key":f"{resultHash}"})



        with open("Telefoongesprek.mp3", "wb") as f:
            f.write(Telefoongesprek.content)

        src = "Telefoongesprek.mp3"
        dst = "Telefoongesprek.wav"

        sound = AudioSegment.from_file(src)
        sound.export(dst, format="wav")


        def speech_recognize_continuous_from_file():
            speech_config = speechsdk.SpeechConfig(subscription="*", region="*")
            speech_config.speech_recognition_language = "nl-NL"
            audio_config = speechsdk.audio.AudioConfig(filename="Telefoongesprek.wav")

            speech_recognizer = speechsdk.SpeechRecognizer(speech_config=speech_config, audio_config=audio_config)

            done = False

            def stop_cb(evt):
                print('CLOSING on {}'.format(evt))
                nonlocal done
                done = True

            all_results = []
            def handle_final_result(evt):
                all_results.append(evt.result.text)
            speech_recognizer.recognized.connect(handle_final_result)
            speech_recognizer.session_started.connect(handle_final_result)
            speech_recognizer.session_stopped.connect(handle_final_result)
            speech_recognizer.canceled.connect(handle_final_result)
            speech_recognizer.session_stopped.connect(stop_cb)
            speech_recognizer.canceled.connect(stop_cb)

            speech_recognizer.start_continuous_recognition()
            while not done:
                time.sleep(.5)

            speech_recognizer.stop_continuous_recognition()

            print(all_results)

            telefoongesprek = str(all_results)
            filename = f"C:\\Users\\Beau\\Contact-verkeer\\contact-verkeer\\telefoon\\STT Transcriptions\\Telefoongesprek#{OID}.txt"
            file = open(filename, "w")
            file.write(telefoongesprek)
            file.close()


        speech_recognize_continuous_from_file()
        cursor.close()
        del cursor

        conn.close()

except Exception as e:
    print("Error: %s" % e)

一切都彼此分开，但我只是不知道该如何放置循环和我应该使用的循环(For/While循环)。在这里，我试图循环一个数组，但我不这样做，这是正确的。

错误消息:解码失败。ffmpeg返回错误代码:1 mp3 @ 000001cb8c57e0o0无法读取帧大小:无法查找到1073。

这意味着我的azure函数找不到mp3文件，这意味着"Mp3 to Wav“转换不起作用。

提前感谢！

Answer 1

如果我理解你的问题，你有一个有很多电话细节的数据库。每行中的字段值之一用于创建关联的mp3文件。您希望在数据库中的每个mp3文件上使用azure对文本进行演讲。

所以你可以用两种方式来做：

1. 遍历数据库中的所有行，并将所有的associted文件创建到本地磁盘中的一个文件夹中，并以OID作为您的文件名。
2. 然后编写另一个循环来遍历该文件夹，并将用于转录的文件发送到Azure语音文本服务。

另一种技术是在一个循环中完成所有事情，就像您所展示的方式一样，这需要进行一些修正。

好的，现在这个部分已经清楚了，我们可以进入演讲到文本部分。因此，azure允许您发送压缩格式进行转录，这意味着您实际上不需要将它转换为wav文件。

请看下面修改后的代码：

# code snippet borrowed from azure samples
def speech_recognize_continuous_from_file(filename):
    class BinaryFileReaderCallback(speechsdk.audio.PullAudioInputStreamCallback):
        def __init__(self, filename: str):
            super().__init__()
            self._file_h = open(filename, "rb")

        def read(self, buffer: memoryview) -> int:
            try:
                size = buffer.nbytes
                frames = self._file_h.read(size)

                buffer[:len(frames)] = frames

                return len(frames)
            except Exception as ex:
                print('Exception in `read`: {}'.format(ex))
                raise

        def close(self) -> None:
            print('closing file')
            try:
                self._file_h.close()
            except Exception as ex:
                print('Exception in `close`: {}'.format(ex))
                raise

    # Creates an audio stream format. For an example we are using MP3 compressed file here
    compressed_format = speechsdk.audio.AudioStreamFormat(compressed_stream_format=speechsdk.AudioStreamContainerFormat.MP3)
    callback = BinaryFileReaderCallback(filename=filename)

    stream = speechsdk.audio.PullAudioInputStream(stream_format=compressed_format, pull_stream_callback=callback)

    speech_config = speechsdk.SpeechConfig(subscription="*", region="*")
    speech_config.speech_recognition_language = "nl-NL"
    audio_config = speechsdk.audio.AudioConfig(stream=stream)

    # Creates a speech recognizer using a file as audio input, also specify the speech language
    speech_recognizer = speechsdk.SpeechRecognizer(speech_config, audio_config)

    done = False

    def stop_cb(evt):
        print('CLOSING on {}'.format(evt))
        nonlocal done
        done = True

    all_results = []

    def handle_final_result(evt):
        all_results.append(evt.result.text)

    speech_recognizer.recognized.connect(handle_final_result)
    speech_recognizer.session_started.connect(handle_final_result)
    speech_recognizer.session_stopped.connect(handle_final_result)
    speech_recognizer.canceled.connect(handle_final_result)
    speech_recognizer.session_stopped.connect(stop_cb)
    speech_recognizer.canceled.connect(stop_cb)

    speech_recognizer.start_continuous_recognition()
    while not done:
        time.sleep(.5)

    speech_recognizer.stop_continuous_recognition()

    print(all_results)

    telefoongesprek = str(all_results)
    filename = f"C:\\Users\\Beau\\Contact-verkeer\\contact-verkeer\\telefoon\\STT Transcriptions\\Telefoongesprek#{OID}.txt"
    file = open(filename, "w")
    file.write(telefoongesprek)
    file.close()

try:
    CONNECTION_STRING = 'DRIVER='+driver+';SERVER='+server+';DATABASE='+databaseName+';UID='+username+';PWD='+ password

    conn = pyodbc.connect(CONNECTION_STRING)

    cursor = conn.cursor()
    storedproc = "* = *'"
    cursor.execute(storedproc)
    row = cursor.fetchone()
    # loop through the rows
    while row:
        array = [(int(row[1]))]

        i = 0
        while i<len(array):
            OID = (array[i])
            i = i + 1
            print(OID)

        string = f"{OID}*"
        encoded = string.encode()
        result = hashlib.sha256(encoded)
        resultHash = (result.hexdigest())

        telefoongesprek_response = requests.get(f"*{OID}", headers={f"api-key":f"{resultHash}"})

        # save the file to local disk as mp3
        with open("Telefoongesprek.mp3", "wb") as f:
            f.write(telefoongesprek_response.content)

        # do the speech to text on the mp3 file
        speech_recognize_continuous_from_file(f.name)

        # fetch the next row
        row = cursor.fetchone()

    cursor.close()
    del cursor
    conn.close()
except Exception as e:
    print("Error: %s" % e)

我还没有测试这个完整的代码，因为我没有数据库连接。请随时修改您的用例，如果您有任何问题，请告诉我。