reproducir - Detecta y graba audio en Python

pyaudio tutorial

Question

Necesito capturar clips de audio como archivos WAV que luego puedo pasar a otro bit de python para su procesamiento. El problema es que necesito determinar cuándo hay audio presente y luego grabarlo, detenerlo cuando esté en silencio y luego pasar ese archivo al módulo de procesamiento.

Estoy pensando que con el módulo de ondas debería ser posible detectar cuándo hay silencio puro y descartarlo; tan pronto como se detecte algo que no sea silencio, empiece a grabar, luego, cuando la línea vuelva a sonar silenciosa, detenga la grabación.

Simplemente no puedo entenderlo, ¿alguien puede ayudarme a comenzar con un ejemplo básico?

Answer 1

Como seguimiento de la respuesta de Nick Fortescue, aquí hay un ejemplo más completo de cómo grabar desde el micrófono y procesar los datos resultantes:

from sys import byteorder
from array import array
from struct import pack

import pyaudio
import wave

THRESHOLD = 500
CHUNK_SIZE = 1024
FORMAT = pyaudio.paInt16
RATE = 44100

def is_silent(snd_data):
    "Returns ''True'' if below the ''silent'' threshold"
    return max(snd_data) < THRESHOLD

def normalize(snd_data):
    "Average the volume out"
    MAXIMUM = 16384
    times = float(MAXIMUM)/max(abs(i) for i in snd_data)

    r = array(''h'')
    for i in snd_data:
        r.append(int(i*times))
    return r

def trim(snd_data):
    "Trim the blank spots at the start and end"
    def _trim(snd_data):
        snd_started = False
        r = array(''h'')

        for i in snd_data:
            if not snd_started and abs(i)>THRESHOLD:
                snd_started = True
                r.append(i)

            elif snd_started:
                r.append(i)
        return r

    # Trim to the left
    snd_data = _trim(snd_data)

    # Trim to the right
    snd_data.reverse()
    snd_data = _trim(snd_data)
    snd_data.reverse()
    return snd_data

def add_silence(snd_data, seconds):
    "Add silence to the start and end of ''snd_data'' of length ''seconds'' (float)"
    r = array(''h'', [0 for i in xrange(int(seconds*RATE))])
    r.extend(snd_data)
    r.extend([0 for i in xrange(int(seconds*RATE))])
    return r

def record():
    """
    Record a word or words from the microphone and 
    return the data as an array of signed shorts.

    Normalizes the audio, trims silence from the 
    start and end, and pads with 0.5 seconds of 
    blank sound to make sure VLC et al can play 
    it without getting chopped off.
    """
    p = pyaudio.PyAudio()
    stream = p.open(format=FORMAT, channels=1, rate=RATE,
        input=True, output=True,
        frames_per_buffer=CHUNK_SIZE)

    num_silent = 0
    snd_started = False

    r = array(''h'')

    while 1:
        # little endian, signed short
        snd_data = array(''h'', stream.read(CHUNK_SIZE))
        if byteorder == ''big'':
            snd_data.byteswap()
        r.extend(snd_data)

        silent = is_silent(snd_data)

        if silent and snd_started:
            num_silent += 1
        elif not silent and not snd_started:
            snd_started = True

        if snd_started and num_silent > 30:
            break

    sample_width = p.get_sample_size(FORMAT)
    stream.stop_stream()
    stream.close()
    p.terminate()

    r = normalize(r)
    r = trim(r)
    r = add_silence(r, 0.5)
    return sample_width, r

def record_to_file(path):
    "Records from the microphone and outputs the resulting data to ''path''"
    sample_width, data = record()
    data = pack(''<'' + (''h''*len(data)), *data)

    wf = wave.open(path, ''wb'')
    wf.setnchannels(1)
    wf.setsampwidth(sample_width)
    wf.setframerate(RATE)
    wf.writeframes(data)
    wf.close()

if __name__ == ''__main__'':
    print("please speak a word into the microphone")
    record_to_file(''demo.wav'')
    print("done - result written to demo.wav")

Answer 2

Creo que el módulo WAVE no admite la grabación, solo procesa archivos existentes. Es posible que desee ver PyAudio para realmente grabar. WAV es sobre el formato de archivo más simple del mundo. En paInt16, solo obtiene un entero con signo que representa un nivel, y más cerca de 0 es más silencioso. No puedo recordar si los archivos WAV son byte alto primero o byte bajo, pero algo así debería funcionar (lo siento, no soy realmente un programador python:

from array import array

# you''ll probably want to experiment on threshold
# depends how noisy the signal
threshold = 10 
max_value = 0

as_ints = array(''h'', data)
max_value = max(as_ints)
if max_value > threshold:
    # not silence

Código de PyAudio para grabación guardado para referencia:

import pyaudio
import sys

chunk = 1024
FORMAT = pyaudio.paInt16
CHANNELS = 1
RATE = 44100
RECORD_SECONDS = 5

p = pyaudio.PyAudio()

stream = p.open(format=FORMAT,
                channels=CHANNELS, 
                rate=RATE, 
                input=True,
                output=True,
                frames_per_buffer=chunk)

print "* recording"
for i in range(0, 44100 / chunk * RECORD_SECONDS):
    data = stream.read(chunk)
    # check for silence here by comparing the level with 0 (or some threshold) for 
    # the contents of data.
    # then write data or not to a file

print "* done"

stream.stop_stream()
stream.close()
p.terminate()

Answer 3

El sitio web pyaudio tiene muchos ejemplos que son bastante cortos y claros: PyAudio

Answer 4

Es posible que desee mirar csounds , también. Tiene varias API, incluyendo Python. Es posible que pueda interactuar con una interfaz AD y recopilar muestras de sonido.

Answer 5

Gracias a cryo por la versión mejorada, basé mi código probado a continuación:

#Instead of adding silence at start and end of recording (values=0) I add the original audio . This makes audio sound more natural as volume is >0. See trim()
#I also fixed issue with the previous code - accumulated silence counter needs to be cleared once recording is resumed.

from array import array
from struct import pack
from sys import byteorder
import copy
import pyaudio
import wave

THRESHOLD = 500  # audio levels not normalised.
CHUNK_SIZE = 1024
SILENT_CHUNKS = 3 * 44100 / 1024  # about 3sec
FORMAT = pyaudio.paInt16
FRAME_MAX_VALUE = 2 ** 15 - 1
NORMALIZE_MINUS_ONE_dB = 10 ** (-1.0 / 20)
RATE = 44100
CHANNELS = 1
TRIM_APPEND = RATE / 4

def is_silent(data_chunk):
    """Returns ''True'' if below the ''silent'' threshold"""
    return max(data_chunk) < THRESHOLD

def normalize(data_all):
    """Amplify the volume out to max -1dB"""
    # MAXIMUM = 16384
    normalize_factor = (float(NORMALIZE_MINUS_ONE_dB * FRAME_MAX_VALUE)
                        / max(abs(i) for i in data_all))

    r = array(''h'')
    for i in data_all:
        r.append(int(i * normalize_factor))
    return r

def trim(data_all):
    _from = 0
    _to = len(data_all) - 1
    for i, b in enumerate(data_all):
        if abs(b) > THRESHOLD:
            _from = max(0, i - TRIM_APPEND)
            break

    for i, b in enumerate(reversed(data_all)):
        if abs(b) > THRESHOLD:
            _to = min(len(data_all) - 1, len(data_all) - 1 - i + TRIM_APPEND)
            break

    return copy.deepcopy(data_all[_from:(_to + 1)])

def record():
    """Record a word or words from the microphone and 
    return the data as an array of signed shorts."""

    p = pyaudio.PyAudio()
    stream = p.open(format=FORMAT, channels=CHANNELS, rate=RATE, input=True, output=True, frames_per_buffer=CHUNK_SIZE)

    silent_chunks = 0
    audio_started = False
    data_all = array(''h'')

    while True:
        # little endian, signed short
        data_chunk = array(''h'', stream.read(CHUNK_SIZE))
        if byteorder == ''big'':
            data_chunk.byteswap()
        data_all.extend(data_chunk)

        silent = is_silent(data_chunk)

        if audio_started:
            if silent:
                silent_chunks += 1
                if silent_chunks > SILENT_CHUNKS:
                    break
            else: 
                silent_chunks = 0
        elif not silent:
            audio_started = True              

    sample_width = p.get_sample_size(FORMAT)
    stream.stop_stream()
    stream.close()
    p.terminate()

    data_all = trim(data_all)  # we trim before normalize as threshhold applies to un-normalized wave (as well as is_silent() function)
    data_all = normalize(data_all)
    return sample_width, data_all

def record_to_file(path):
    "Records from the microphone and outputs the resulting data to ''path''"
    sample_width, data = record()
    data = pack(''<'' + (''h'' * len(data)), *data)

    wave_file = wave.open(path, ''wb'')
    wave_file.setnchannels(CHANNELS)
    wave_file.setsampwidth(sample_width)
    wave_file.setframerate(RATE)
    wave_file.writeframes(data)
    wave_file.close()

if __name__ == ''__main__'':
    print("Wait in silence to begin recording; wait in silence to terminate")
    record_to_file(''demo.wav'')
    print("done - result written to demo.wav")

Answer 6

import pyaudio
import wave
from array import array

FORMAT=pyaudio.paInt16
CHANNELS=2
RATE=44100
CHUNK=1024
RECORD_SECONDS=15
FILE_NAME="RECORDING.wav"

audio=pyaudio.PyAudio() #instantiate the pyaudio

#recording prerequisites
stream=audio.open(format=FORMAT,channels=CHANNELS, 
                  rate=RATE,
                  input=True,
                  frames_per_buffer=CHUNK)

#starting recording
frames=[]

for i in range(0,int(RATE/CHUNK*RECORD_SECONDS)):
    data=stream.read(CHUNK)
    data_chunk=array(''h'',data)
    vol=max(data_chunk)
    if(vol>=500):
        print("something said")
        frames.append(data)
    else:
        print("nothing")
    print("/n")


#end of recording
stream.stop_stream()
stream.close()
audio.terminate()
#writing to file
wavfile=wave.open(FILE_NAME,''wb'')
wavfile.setnchannels(CHANNELS)
wavfile.setsampwidth(audio.get_sample_size(FORMAT))
wavfile.setframerate(RATE)
wavfile.writeframes(b''''.join(frames))#append frames recorded to file
wavfile.close()

Creo que esto ayudará. Es una secuencia de comandos simple que verificará si hay un silencio o no. Si se detecta silencio, no se grabará, de lo contrario, se grabará.