1# Copyright 2018 The TensorFlow Authors. All Rights Reserved. 2# 3# Licensed under the Apache License, Version 2.0 (the "License"); 4# you may not use this file except in compliance with the License. 5# You may obtain a copy of the License at 6# 7# http://www.apache.org/licenses/LICENSE-2.0 8# 9# Unless required by applicable law or agreed to in writing, software 10# distributed under the License is distributed on an "AS IS" BASIS, 11# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. 12# See the License for the specific language governing permissions and 13# limitations under the License. 14# ============================================================================== 15"""AudioMicrofrontend Op creates filterbanks from audio data.""" 16 17from tensorflow.lite.experimental.microfrontend.ops import gen_audio_microfrontend_op 18from tensorflow.python.framework import dtypes 19from tensorflow.python.framework import load_library 20from tensorflow.python.framework import ops 21from tensorflow.python.ops import array_ops 22from tensorflow.python.platform import resource_loader 23from tensorflow.python.util.tf_export import tf_export 24 25_audio_microfrontend_op = load_library.load_op_library( 26 resource_loader.get_path_to_datafile("_audio_microfrontend_op.so")) 27 28 29@tf_export("lite.experimental.microfrontend.python.ops.audio_microfrontend") 30def audio_microfrontend(audio, 31 sample_rate=16000, 32 window_size=25, 33 window_step=10, 34 num_channels=32, 35 upper_band_limit=7500.0, 36 lower_band_limit=125.0, 37 smoothing_bits=10, 38 even_smoothing=0.025, 39 odd_smoothing=0.06, 40 min_signal_remaining=0.05, 41 enable_pcan=True, 42 pcan_strength=0.95, 43 pcan_offset=80.0, 44 gain_bits=21, 45 enable_log=True, 46 scale_shift=6, 47 left_context=0, 48 right_context=0, 49 frame_stride=1, 50 zero_padding=False, 51 out_scale=1, 52 out_type=dtypes.uint16): 53 """Audio Microfrontend Op. 54 55 This Op converts a sequence of audio data into one or more 56 feature vectors containing filterbanks of the input. The 57 conversion process uses a lightweight library to perform: 58 59 1. A slicing window function 60 2. Short-time FFTs 61 3. Filterbank calculations 62 4. Noise reduction 63 5. PCAN Auto Gain Control 64 6. Logarithmic scaling 65 66 Args: 67 audio: 1D Tensor, int16 audio data in temporal ordering. 68 sample_rate: Integer, the sample rate of the audio in Hz. 69 window_size: Integer, length of desired time frames in ms. 70 window_step: Integer, length of step size for the next frame in ms. 71 num_channels: Integer, the number of filterbank channels to use. 72 upper_band_limit: Float, the highest frequency included in the filterbanks. 73 lower_band_limit: Float, the lowest frequency included in the filterbanks. 74 smoothing_bits: Int, scale up signal by 2^(smoothing_bits) before reduction. 75 even_smoothing: Float, smoothing coefficient for even-numbered channels. 76 odd_smoothing: Float, smoothing coefficient for odd-numbered channels. 77 min_signal_remaining: Float, fraction of signal to preserve in smoothing. 78 enable_pcan: Bool, enable PCAN auto gain control. 79 pcan_strength: Float, gain normalization exponent. 80 pcan_offset: Float, positive value added in the normalization denominator. 81 gain_bits: Int, number of fractional bits in the gain. 82 enable_log: Bool, enable logarithmic scaling of filterbanks. 83 scale_shift: Integer, scale filterbanks by 2^(scale_shift). 84 left_context: Integer, number of preceding frames to attach to each frame. 85 right_context: Integer, number of preceding frames to attach to each frame. 86 frame_stride: Integer, M frames to skip over, where output[n] = frame[n*M]. 87 zero_padding: Bool, if left/right context is out-of-bounds, attach frame of 88 zeroes. Otherwise, frame[0] or frame[size-1] will be copied. 89 out_scale: Integer, divide all filterbanks by this number. 90 out_type: DType, type of the output Tensor, defaults to UINT16. 91 92 Returns: 93 filterbanks: 2D Tensor, each row is a time frame, each column is a channel. 94 95 Raises: 96 ValueError: If the audio tensor is not explicitly a vector. 97 """ 98 audio_shape = audio.shape 99 if audio_shape.ndims is None: 100 raise ValueError("Input to `AudioMicrofrontend` should have known rank.") 101 if len(audio_shape) > 1: 102 audio = array_ops.reshape(audio, [-1]) 103 104 return gen_audio_microfrontend_op.audio_microfrontend( 105 audio, sample_rate, window_size, window_step, num_channels, 106 upper_band_limit, lower_band_limit, smoothing_bits, even_smoothing, 107 odd_smoothing, min_signal_remaining, enable_pcan, pcan_strength, 108 pcan_offset, gain_bits, enable_log, scale_shift, left_context, 109 right_context, frame_stride, zero_padding, out_scale, out_type) 110 111 112ops.NotDifferentiable("AudioMicrofrontend") 113