amplitude normalization in create_fb_matrix

🐛 Not necessarily a Bug

Not exactly a bug, but I think it makes more sense if the triangular Mel filterbanks are area-normalized, as opposed to the current behavior where they are height-normalized.

To Reproduce / Expected behavior

Steps to reproduce the behavior:

import matplotlib.pyplot as plt
import torchaudio
import librosa

plt.figure(figsize=(16, 8))
plt.subplot(2, 1, 1)
plt.plot(torchaudio.transforms.MelScale(n_stft=1025, sample_rate=16000).fb.detach().cpu().numpy())
plt.title('torchaudio Mel filterbanks')

plt.subplot(2, 1, 2)
plt.plot(librosa.filters.mel(sr=16000, n_fft=2048).transpose())
plt.title('librosa Mel filterbanks')
plt.show()

The former has an advantage of preserving the energy similar to the STFT, while the latter keeps the overall spectral envelope unchanged.

If this is an intended behavior, feel free to close this issue. Thanks!

Environment

• What commands did you used to install torchaudio (conda/pip/build from source)?

I did pip install torchaudio -f https://download.pytorch.org/whl/torch_stable.html, following README.md

• What does torchaudio.__version__ print? (If applicable)

‘0.3.0’

Please copy and paste the output from our environment collection script.

Collecting environment information...
PyTorch version: 1.2.0
Is debug build: No
CUDA used to build PyTorch: 10.0.130

OS: Ubuntu 16.04.5 LTS
GCC version: (Ubuntu 5.4.0-6ubuntu1~16.04.11) 5.4.0 20160609
CMake version: version 3.11.1

Python version: 3.7
Is CUDA available: Yes
CUDA runtime version: 10.0.130
GPU models and configuration:
GPU 0: Tesla V100-SXM2-16GB
GPU 1: Tesla V100-SXM2-16GB
GPU 2: Tesla V100-SXM2-16GB
GPU 3: Tesla V100-SXM2-16GB
GPU 4: Tesla V100-SXM2-16GB
GPU 5: Tesla V100-SXM2-16GB
GPU 6: Tesla V100-SXM2-16GB
GPU 7: Tesla V100-SXM2-16GB

Nvidia driver version: 410.79
cuDNN version: /usr/lib/x86_64-linux-gnu/libcudnn.so.7.4.2

Versions of relevant libraries:
[pip3] numpy==1.16.5
[pip3] pytorch-memlab==0.0.3
[pip3] torch==1.2.0
[pip3] torch-bst==0.0.0
[pip3] torch-data==0.0.1
[pip3] torchaudio==0.3.0
[pip3] torchvision==0.4.0
[conda] blas                      1.0                         mkl
[conda] faiss-gpu                 1.5.3            py37h1a5d453_0    pytorch
[conda] mkl                       2019.4                      243
[conda] mkl-service               2.3.0            py37he904b0f_0
[conda] mkl_fft                   1.0.14           py37ha843d7b_0
[conda] mkl_random                1.0.2            py37hd81dba3_0
[conda] pytorch-memlab            0.0.3                    pypi_0    pypi
[conda] torch                     1.2.0                    pypi_0    pypi
[conda] torch-bst                 0.0.0                     dev_0    <develop>
[conda] torch-data                0.0.1                     dev_0    <develop>
[conda] torchaudio                0.3.0                    pypi_0    pypi
[conda] torchvision               0.4.0                    pypi_0    pypi

[keunwoochoi]

+1 for this!

[vincentqb]

This is implemented in #589.