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用python识别语音中的文字

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接着上一篇，第二步，用python识别语音中的文字。

基本使用

前提准备：必须是wav格式

安装speech recognition包

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python3 -m pip install SpeechRecognition

使用

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import speech_recognition as sr

filename = "01.wav"

# initialize the recognizer
r = sr.Recognizer()

# open the file
with sr.AudioFile(filename) as source:
    # listen for the data (load audio to memory)
    audio_data = r.record(source)
    # recognize (convert from speech to text)
    text = r.recognize_google(audio_data)
    print(text)

就可以啦！

如果想要改变语言不是识别英语的话

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#Adding french langauge option
text = r.recognize_google(audio_text, language = "fr-FR")

不过如果语音很大的话会很慢，所以可以使用将它拆解的方式拆开。

长语音识别

安装pydub

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python3 -m pip install pydub

使用

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# importing libraries 
import speech_recognition as sr 
import os 
from pydub import AudioSegment
from pydub.silence import split_on_silence

# create a speech recognition object
r = sr.Recognizer()

# a function that splits the audio file into chunks
# and applies speech recognition
def get_large_audio_transcription(path):
    """
    Splitting the large audio file into chunks
    and apply speech recognition on each of these chunks
    """
    # open the audio file using pydub
    sound = AudioSegment.from_wav(path)  
    # split audio sound where silence is 700 miliseconds or more and get chunks
    chunks = split_on_silence(sound,
        # experiment with this value for your target audio file
        min_silence_len = 500,
        # adjust this per requirement
        silence_thresh = sound.dBFS-14,
        # keep the silence for 1 second, adjustable as well
        keep_silence=500,
    )
    folder_name = "audio-chunks"
    # create a directory to store the audio chunks
    if not os.path.isdir(folder_name):
        os.mkdir(folder_name)
    whole_text = ""
    # process each chunk 
    for i, audio_chunk in enumerate(chunks, start=1):
        # export audio chunk and save it in
        # the `folder_name` directory.
        chunk_filename = os.path.join(folder_name, f"chunk{i}.wav")
        audio_chunk.export(chunk_filename, format="wav")
        # recognize the chunk
        with sr.AudioFile(chunk_filename) as source:
            audio_listened = r.record(source)
            # try converting it to text
            try:
                text = r.recognize_google(audio_listened)
            except sr.UnknownValueError as e:
                print("Error:", str(e))
            else:
                text = f"{text.capitalize()}. "
                print(chunk_filename, ":", text)
                whole_text += text
    # return the text for all chunks detected
    return whole_text
  
get_large_audio_transcription('01.wav')

录音识别

安装

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python3 -m pip install PyAudio

使用

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# import library

import speech_recognition as sr

# Initialize recognizer class (for recognizing the speech)

r = sr.Recognizer()

# Reading Microphone as source
# listening the speech and store in audio_text variable

with sr.Microphone() as source:
    print("Talk")
    audio_text = r.listen(source)
    print("Time over, thanks")
# recoginize_() method will throw a request error if the API is unreachable, hence using exception handling
    
    try:
        # using google speech recognition
        print("Text: "+r.recognize_google(audio_text))
    except:
         print("Sorry, I did not get that")

如果说的不是英语

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# Adding "tamil language"
print(“Text: “+r.recognize_google(audio_text, language = “ta-IN”))

Reference

Easy Speech-to-Text with Python

How to Convert Speech to Text in Python