![]() to_wav ( f "examples/samples/guitar_16k_reverb_ s". add_microphone_array ( mic_locs ) # Run the simulation (this will also build the RIR automatically) room. c_, , # mic 1 # mic 2 ] # finally place the array in the room room. add_source (, signal = audio, delay = 0.5 ) # define the locations of the microphones mic_locs = np. Material ( e_absorption ), max_order = max_order ) # place the source in the room room. ShoeBox ( room_dim, fs = fs, materials = pra. inverse_sabine ( rt60_tgt, room_dim ) # Create the room room = pra. read ( "examples/samples/guitar_16k.wav" ) # We invert Sabine's formula to obtain the parameters for the ISM simulator e_absorption, max_order = pra. ![]() Import numpy as np import matplotlib.pyplot as plt import pyroomacoustics as pra from scipy.io import wavfile # The desired reverberation time and dimensions of the room rt60_tgt = 0.3 # seconds room_dim = # meters # import a mono wavfile as the source signal # the sampling frequency should match that of the room fs, audio = wavfile. Microphones can optionally operate at a different samplingįrequency a rate conversion is done in this case. Since the simulation is done onĭiscrete-time signals, a sampling frequency is specified for the room and the The microphone signals are then created by convolving audio samples associated Ray tracingīetter capture the later reflections and can also model effects such as Hybrid simulator based on image source method (ISM) and ray tracing (RT), , is also available. Image source which considers the walls as perfect reflectors. (RIR) between the sources and microphones. Then, a simulation method is used to create artificial room impulse responses ![]() ![]() Sources and a microphone array are attached. Simulation scenario is created by first defining a room to which a few sound ![]()
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