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我有一个项目需要获取记录的文件，然后通过代码处理并从文件中提取文本并将提取的文件与其他文本匹配并验证它。我的问题是：我不能在代码中使用记录的文件并且它不读取文件

init 函数是代码的基础。

验证功能确认匹配的语音和文本。

import argparse
import json
import os
import queue
import random
import sys
from difflib import SequenceMatcher
import numpy as np
import sounddevice as sd
import vosk

q = queue.Queue()

def int_or_str(text):
    """Helper function for argument parsing."""
    try:
        return int(text)
    except ValueError:
        return text


def callback(indata, frames, time, status):
    """This is called (from a separate thread) for each audio block."""
    if status:
        print(status, file=sys.stderr)
    q.put(bytes(indata))



def init():
    parser = argparse.ArgumentParser(add_help=False)
    parser.add_argument(
        '-l', '--list-devices', action='store_true',
        help='show list of audio devices and exit')
    args, remaining = parser.parse_known_args()
    if args.list_devices:
        print(sd.query_devices())
        parser.exit(0)
    parser = argparse.ArgumentParser(
        description=__doc__,
        formatter_class=argparse.RawDescriptionHelpFormatter,
        parents=[parser])
    parser.add_argument(
        '-f', '--filename', type=str, metavar='FILENAME',
        help='audio file to store recording to')
    parser.add_argument(
        '-m', '--model', type=str, metavar='MODEL_PATH',
        help='Path to the model')
    parser.add_argument(
        '-d', '--device', type=int_or_str,
        help='input device (numeric ID or substring)')
    parser.add_argument(
        '-r', '--samplerate', type=int, help='sampling rate')
    args = parser.parse_args(remaining)
    try:
        if args.model is None:
            args.model = "model"
        if not os.path.exists(args.model):
            print("Please download a model for your language from https://alphacephei.com/vosk/models")
            print("and unpack as 'model' in the current folder.")
            parser.exit(0)
        if args.samplerate is None:
            device_info = sd.query_devices(args.device, 'input')
            # soundfile expects an int, sounddevice provides a float:
            args.samplerate = int(device_info['default_samplerate'])

        model = vosk.Model(args.model)

        if args.filename:
            dump_fn = open(args.filename, "wb")
        else:
            dump_fn = None

        
    except KeyboardInterrupt:
        print('\nDone')
        parser.exit(0)
    except Exception as e:
        parser.exit(type(e).__name__ + ': ' + str(e))

    return model, args
def verify(random_sentence, model, args):
    num, T_num, F_num, num_word = 0, 0, 0, 1
    with sd.RawInputStream(samplerate=args.samplerate, blocksize=8000, device=args.device, dtype='int16',
                           channels=1, callback=callback):
        rec = vosk.KaldiRecognizer(model, args.samplerate)
        print("{}) ".format(num_word), random_sentence, end='\n')
        print('=' * 30, end='\n')
        run = True
        while run:
            data = q.get()
            if rec.AcceptWaveform(data):
                res = json.loads(rec.FinalResult())
                res['text'] = res['text'].replace('ي', 'ی')             
                if SequenceMatcher(None, random_sentence, res['text']).ratio() > 0.65:                    
                    T_num, num, num_word += 1
                    
                else:
                    F_num, num, num_word += 1
                    
                run = False

    print('=' * 30)
    print('True Cases : {}\n False Cases : {}'.format(T_num, F_num))


if __name__ == "__main__":
    model, args = init()
    verify(random_sentences, model, args)
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1 回答 1

0

我一直在做一个类似的项目。我修改 了来自 VOSK Git repo 的代码并编写了以下函数，该函数将文件名/路径作为输入并输出捕获的文本。有时，当音频文件中有较长的停顿（~秒）时，返回的文本将是一个空字符串。为了解决这个问题，我不得不编写额外的代码来挑选出最长的字符串。我可以解决这个问题。

def get_text_from_voice(filename):

    if not os.path.exists("model"):
        print ("Please download the model from https://alphacephei.com/vosk/models and unpack as 'model' in the current folder.")
        exit (1)

    wf = wave.open(filename, "rb")
    if wf.getnchannels() != 1 or wf.getsampwidth() != 2 or wf.getcomptype() != "NONE":
        print ("Audio file must be WAV format mono PCM.")
        exit (1)

    model = Model("model")
    rec = KaldiRecognizer(model, wf.getframerate())
    rec.SetWords(True)

    text_lst =[]
    p_text_lst = []
    p_str = []
    len_p_str = []
    while True:
        data = wf.readframes(4000)
        if len(data) == 0:
            break
        if rec.AcceptWaveform(data):
            text_lst.append(rec.Result())
            print(rec.Result())
        else:
            p_text_lst.append(rec.PartialResult())
            print(rec.PartialResult())

    if len(text_lst) !=0:
        jd = json.loads(text_lst[0])
        txt_str = jd["text"]
        
    elif len(p_text_lst) !=0: 
        for i in range(0,len(p_text_lst)):
            temp_txt_dict = json.loads(p_text_lst[i])
            p_str.append(temp_txt_dict['partial'])
       
        len_p_str = [len(p_str[j]) for j in range(0,len(p_str))]
        max_val = max(len_p_str)
        indx = len_p_str.index(max_val)
        txt_str = p_str[indx]
            
    else:
        txt_str =''

    return txt_str

确保正确的模型存在于同一目录中或放入模型的路径中。另请注意，VOSK 仅接受 wav 单声道 PCM 格式的音频文件。

于 2021-09-07T07:33:04.917 回答