diff options
Diffstat (limited to 'docs/use_cases/noise_reduction.md')
| -rw-r--r-- | docs/use_cases/noise_reduction.md | 25 |
1 files changed, 12 insertions, 13 deletions
diff --git a/docs/use_cases/noise_reduction.md b/docs/use_cases/noise_reduction.md index cd89091..b015492 100644 --- a/docs/use_cases/noise_reduction.md +++ b/docs/use_cases/noise_reduction.md @@ -59,7 +59,7 @@ then `100x22`, representing the gain values to apply to each of the 100 windows. These output gain values can then be applied to each corresponding window of the noisy audio clip, producing a cleaner output. -For more information please refer to the original paper: +For more information please refer to the original paper: [A Hybrid DSP/Deep Learning Approach to Real-Time Full-Band Speech Enhancement](https://arxiv.org/pdf/1709.08243.pdf) ## Post-processing @@ -95,7 +95,7 @@ Dumps 1 MiB worth of data from address `0x80000000` to the file `output.bin`. ### Dumping post-processed results for all inferences The Noise Reduction application uses the memory address specified by -`noise_reduction_MEM_DUMP_BASE_ADDR` as a buffer to store post-processed results from all inferences. +`noise_reduction_MEM_DUMP_BASE_ADDR` as a buffer to store post-processed results from all inferences. The maximum size of this buffer is set by the parameter `noise_reduction_MEM_DUMP_LEN` which defaults to 1 MiB. @@ -114,7 +114,7 @@ INFO - Copied 960 bytes to 0x8001fa54 ``` In the preceding output we can see that it starts at the default address of -`0x80000000` where some header information is dumped. Then, after the first inference 960 bytes +`0x80000000` where some header information is dumped. Then, after the first inference 960 bytes (480 INT16 values) are written to the first address after the dumped header `0x80000014`. Each inference afterward will then write another 960 bytes to the next address and so on until all inferences are complete. @@ -153,15 +153,15 @@ case adds: WAV file, to be used in the application. The default value points to the `resources/noise_reduction/samples` folder containing the delivered set of audio clips. -- `noise_reduction_AUDIO_RATE`: The input data sampling rate. Each audio file from `noise_reduction_FILE_PATH` is +- `noise_reduction_AUDIO_RATE`: The input data sampling rate. Each audio file from `noise_reduction_FILE_PATH` is preprocessed during the build to match the NN model input requirements. The default value is `48000`. - `noise_reduction_AUDIO_MONO`: If set to `ON`, then the audio data is converted to mono. The default value is `ON`. -- `noise_reduction_AUDIO_OFFSET`: Begins loading audio data and starts from this specified offset, defined in seconds. +- `noise_reduction_AUDIO_OFFSET`: Begins loading audio data and starts from this specified offset, defined in seconds. The default value is set to `0`. -- `noise_reduction_AUDIO_DURATION`: The length of the audio data to be used in the application in seconds. +- `noise_reduction_AUDIO_DURATION`: The length of the audio data to be used in the application in seconds. The default is `0`, meaning that the whole audio file is used. - `noise_reduction_AUDIO_MIN_SAMPLES`: Minimum number of samples required by the network model. If the audio clip is shorter than @@ -208,7 +208,6 @@ For more notes, please refer to: - [Configuring with custom TPIP dependencies](../sections/building.md#configuring-with-custom-tpip-dependencies) - [Using Arm Compiler](../sections/building.md#using-arm-compiler) - [Configuring the build for simple-platform](../sections/building.md#configuring-the-build-for-simple_platform) -- [Working with model debugger from Arm Fast Model Tools](../sections/building.md#working-with-model-debugger-from-arm-fast-model-tools) - [Building for different Ethos-U variants](../sections/building.md#building-for-different-ethos_u-npu-variants) > **Note:** If you are rebuilding with changed parameters values, it is highly advised that you @@ -255,7 +254,7 @@ Based on the preceding output, the files contain the following information: ### Add custom input To run with inputs different to the ones supplied, the parameter `noise_reduction_FILE_PATH` can be -pointed to a WAV file, or a directory containing WAV files. Once you have a directory with WAV files, +pointed to a WAV file, or a directory containing WAV files. Once you have a directory with WAV files, run the following command: ```commandline @@ -285,7 +284,7 @@ cmake .. \ > **Note** Changing the neural network model often also requires the pre-processing implementation > to be changed. Please refer to: > [How the default neural network model works](./noise_reduction.md#how-the-default-neural-network-model-works). - +> > **Note:** Before re-running the CMake command, clean the build directory. The `.tflite` model file, which is pointed to by `noise_reduction_MODEL_TFLITE_PATH`, is converted @@ -380,7 +379,7 @@ Choice: > **Note:** Select the index in the range of supplied WAVs during application build. By default, the pre-built application has three files and indexes from 0-2. -3. “Run noise reduction on all WAVs”: Triggers sequential processing and inference executions on +3. “Run noise reduction on all WAVs”: Triggers sequential processing and inference executions on all baked-in WAV files. 4. “Show NN model info”: Prints information about the model data type, including the input and @@ -418,7 +417,7 @@ Choice: INFO - Quant dimension: 0 INFO - Scale[0] = 0.007843 INFO - ZeroPoint[0] = -1 - INFO - Model OUTPUT tensors: + INFO - Model OUTPUT tensors: INFO - tensor type is INT8 INFO - tensor occupies 96 bytes with dimensions INFO - 0: 1 @@ -493,7 +492,7 @@ INFO - Copied 960 bytes to 0x8001fa54 INFO - Output memory dump of 130580 bytes written at address 0x80000000 INFO - Final results: INFO - Profile for Inference: -INFO - NPU AXI0_RD_DATA_BEAT_RECEIVED beats: 530 +INFO - NPU AXI0_RD_DATA_BEAT_RECEIVED beats: 530 INFO - NPU AXI0_WR_DATA_BEAT_WRITTEN beats: 376 INFO - NPU AXI1_RD_DATA_BEAT_RECEIVED beats: 13911 INFO - NPU ACTIVE cycles: 103870 @@ -503,7 +502,7 @@ INFO - NPU TOTAL cycles: 104514 > **Note:** When running Fast Model, each inference can take several seconds on most systems. -Each inference dumps the post processed output to memory. For further information, please refer to: +Each inference dumps the post processed output to memory. For further information, please refer to: [Dumping post processed results for all inferences](./noise_reduction.md#dumping-post_processed-results-for-all-inferences). The profiling section of the log shows that for this inference: |