Question

我有一个使用speech_recognition包的Python脚本来识别语音并返回所说内容的文本。然而，转录延迟了几秒钟。是否有另一种方法来编写此脚本以返回每个单词，因为它被说出来了？我有另一个脚本来使用pysphinx包，但结果非常不准确。

安装依赖项：

pip install SpeechRecognition
pip install pocketsphinx

脚本1 - 语音到文本的延迟：

import speech_recognition as sr  

# obtain audio from the microphone  
r = sr.Recognizer()  
with sr.Microphone() as source:  
  print("Please wait. Calibrating microphone...")  
  # listen for 5 seconds and create the ambient noise energy level  
  r.adjust_for_ambient_noise(source, duration=5)  
  print("Say something!")  
  audio = r.listen(source)  

# recognize speech using Sphinx  
try:  
  print("Sphinx thinks you said '" + r.recognize_sphinx(audio) + "'")  
except sr.UnknownValueError:  
  print("Sphinx could not understand audio")  
except sr.RequestError as e:  
  print("Sphinx error; {0}".format(e))

脚本2 - 即时不准确的语音转文本：

import os
from pocketsphinx import LiveSpeech, get_model_path
model_path = get_model_path()
speech = LiveSpeech(
verbose=False,
sampling_rate=16000,
buffer_size=2048,
no_search=False,
full_utt=False,
hmm=os.path.join(model_path, 'en-us'),
lm=os.path.join(model_path, 'en-us.lm.bin'),
dic=os.path.join(model_path, 'cmudict-en-us.dict')
)
for phrase in speech: print(phrase)

Answer 1

如果碰巧具有启用CUDA的GPU，则可以尝试Mozilla的DeepSpeech GPU库。它们还具有CPU版本，以防您没有启用CUDA的GPU。 CPU使用DeepSpeech以1.3倍的时间记录音频文件，而在GPU上，速度为0.3倍，即它以0.33秒的时间记录1秒的音频文件。快速入门：

# Create and activate a virtualenv
virtualenv -p python3 $HOME/tmp/deepspeech-gpu-venv/
source $HOME/tmp/deepspeech-gpu-venv/bin/activate

# Install DeepSpeech CUDA enabled package
pip3 install deepspeech-gpu

# Transcribe an audio file.
deepspeech --model deepspeech-0.6.1-models/output_graph.pbmm --lm deepspeech- 
0.6.1-models/lm.binary --trie deepspeech-0.6.1-models/trie --audio audio/2830- 
3980-0043.wav

一些重要说明-Deepspeech-gpu具有一些依赖项，例如tensorflow，CUDA，cuDNN等。因此，请查看其github存储库以获取更多详细信息-https://github.com/mozilla/DeepSpeech

现场语音识别

1 个答案: