"""
""" User selected parameters """
input_wav = "speech.wav"
grain_len = 20 # in milliseconds
grain_over = 0.99 # grain overlap (0,1)
shift_factor = 1.5
# open WAV file
samp_freq, signal = wavfile.read(input_wav)
signal = signal[:,] # get first channel
data_type = signal.dtype
MAX_VAL = np.iinfo(data_type).max
# derived parameters
GRAIN_LEN_SAMP = ms2smp(grain_len, samp_freq)
STRIDE = compute_stride(GRAIN_LEN_SAMP, grain_over)
OVERLAP_LEN = GRAIN_LEN_SAMP-STRIDE
# allocate input and output buffers
input_buffer = np.zeros(STRIDE, dtype=data_type)
output_buffer = np.zeros(STRIDE, dtype=data_type)
# state variables and constants
def init():
# lookup table for tapering window
global WIN
WIN = win_taper(GRAIN_LEN_SAMP, grain_over, data_type)
# lookup table for linear interpolation
from utils import ms2smp, double_len, double_len_taper
f = 100
grain_len = 32 # ms
overlap = 0.3
duration = 100 # ms
disp = 60
fs = 16000
# original
time = np.arange(int(duration * 1e-3 * fs)) / fs
x = np.sin(2 * np.pi * f * time)
# double length
grain_len_samp = ms2smp(grain_len, fs)
x_double = double_len(x, grain_len_samp)
time_double = np.arange(len(x_double)) / fs
# double length with overlap/window
x_double_win, stride_samp, grains = double_len_taper(x, grain_len_samp,
overlap)
stride_len = stride_samp / fs * 1000
time_double_win = np.arange(len(x_double_win)) / fs
# visualize discontinuous
f, (ax1, ax2) = plt.subplots(2, 1)
ax1.plot(time, x)
ax1.grid()
ax1.set_ylabel("Original", fontsize=18)
import numpy as np
from utils import ms2smp, compute_stride, win_taper, build_linear_interp_table
import sounddevice as sd
"""
Real-time pitch shifting with granular synthesis for shift factors <=1.0
"""
""" User selected parameters """
grain_len = 30
grain_over = 0.2
shift_factor = 0.7
data_type = np.int16
# derived parameters
MAX_VAL = np.iinfo(data_type).max
GRAIN_LEN_SAMP = ms2smp(grain_len, 8000)
STRIDE = compute_stride(GRAIN_LEN_SAMP, grain_over)
OVERLAP_LEN = GRAIN_LEN_SAMP - STRIDE
# allocate input and output buffers
input_buffer = np.zeros(STRIDE, dtype=data_type)
output_buffer = np.zeros(STRIDE, dtype=data_type)
# state variables and constants
def init():
# lookup table for tapering window
global WIN
WIN = win_taper(GRAIN_LEN_SAMP, grain_over, data_type)
# lookup table for linear interpolation