def fft_analyzer_select(self, path=path_to_test):
askopenfile = filedialog.askopenfile(filetypes=[("Wave audio files", "*.wav *.wave")], defaultextension=".wav",
initialdir=path)
if not askopenfile is None:
wav = WavFile(askopenfile.name)
result_str = FFTVoiceAnalyzer.analyze(wav, self.processor)
messagebox.showinfo("Result", result_str)
if show_plots:
plot = Plotter("DRA")
plot.add_sub_plot_data("Digitized Recorded Audio", wav.get_one_channel_data(), x_label="Samples",
y_label="Amplitude")
plot.sub_plot_all_horizontal(show=False, save=True)
else:
messagebox.showwarning("Warning", "You should select one file. Please, try again")
def create_files(wav, word_results, items, nbc):
data = wav.get_one_channel_data()
for i in word_results.keys():
starts = word_results[i]['starts']
ends = word_results[i]['ends']
num = 1
for k in range(0, len(starts)):
file_name = 'word' + str(num) + "_" + str(i) + '.wav'
file_items = data[starts[k] * items:ends[k] * items]
if not nbc is None and use_nbc_for_vad:
if len(file_items) > 10000 and nbc.get_class(nbc.get_classes(nbc.classify(
WavFile(samples=WavFile.to_binary(file_items), sample_width=wav.sample_width,
time=1)))) == "speech":
WavFile.write(path_to_vad_results + file_name, file_items, 0)
num += 1
else:
if len(file_items) > 10000:
WavFile.write(path_to_vad_results + file_name, file_items, 0)
num += 1
def create_lib_with_examples(self):
"""
creates new library and adds all files from base folder as items
@return: new Library object
"""
example_waves = WavFile.get_all_waves(get_files(self.base_lib_folder, self.extension))
lib = Library(self.fft, really_transform=self.really_transform)
for i in example_waves:
lib.create_and_add_item_from_wave(i)
return lib
def create_sin_test(time, sample_rate, file_name=None, amplitude=32767, freq_hz=100, is_plot=False):
"""
create test audio file with sin
@param time: length of audio (seconds)
@param sample_rate: sample rate (44100 Hz for example)
@param file_name: name of file for save or None, if you don't wont to save file
@param amplitude: max amplitude
@param freq_hz: dominant frequency
@param is_plot: flag for plot file data
"""
buf_size = sample_rate*time
buffer = list(numpy.zeros(buf_size, int))
for i in range(buf_size):
buffer[i] += int(amplitude * math.sin(float(2 * math.pi * i * freq_hz / sample_rate)))
if is_plot:
plotter = Plotter("Created Sin Test")
plotter.add_sub_plot_data("data", buffer)
plotter.sub_plot_all_horizontal()
if not file_name is None:
WavFile.write(file_name, buffer, time)
