DeepAI AI Chat
Log In Sign Up

Learning Filter Banks Using Deep Learning For Acoustic Signals

by   Shuhui Qu, et al.
Carnegie Mellon University
Stanford University

Designing appropriate features for acoustic event recognition tasks is an active field of research. Expressive features should both improve the performance of the tasks and also be interpret-able. Currently, heuristically designed features based on the domain knowledge requires tremendous effort in hand-crafting, while features extracted through deep network are difficult for human to interpret. In this work, we explore the experience guided learning method for designing acoustic features. This is a novel hybrid approach combining both domain knowledge and purely data driven feature designing. Based on the procedure of log Mel-filter banks, we design a filter bank learning layer. We concatenate this layer with a convolutional neural network (CNN) model. After training the network, the weight of the filter bank learning layer is extracted to facilitate the design of acoustic features. We smooth the trained weight of the learning layer and re-initialize it in filter bank learning layer as audio feature extractor. For the environmental sound recognition task based on the Urban- sound8K dataset, the experience guided learning leads to a 2 extractors (the log Mel-filter bank). The shape of the new filter banks are visualized and explained to prove the effectiveness of the feature design process.


Enhancing Sound Texture in CNN-Based Acoustic Scene Classification

Acoustic scene classification is the task of identifying the scene from ...

Using Filter Banks in Convolutional Neural Networks for Texture Classification

Deep learning has established many new state of the art solutions in the...

Audio-video Emotion Recognition in the Wild using Deep Hybrid Networks

This paper presents an audiovisual-based emotion recognition hybrid netw...

Filter design for small target detection on infrared imagery using normalized-cross-correlation layer

In this paper, we introduce a machine learning approach to the problem o...

Designing Network Design Strategies Through Gradient Path Analysis

Designing a high-efficiency and high-quality expressive network architec...

Interpretable deep learning for guided structure-property explorations in photovoltaics

The performance of an organic photovoltaic device is intricately connect...

Limitations of Source-Filter Coupling In Phonation

The coupling of vocal fold (source) and vocal tract (filter) is one of t...