Chrome Extension
WeChat Mini Program
Use on ChatGLM

Training a Filter-Based Model of the Cochlea in the Context of Pre-Trained Acoustic Models

Louise Coppieters de Gibson,Philip N. Garner

Acoustics(2024)

Cited 0|Views0
No score
Abstract
Auditory research aims in general to lead to understanding of physiological processes. By contrast, the state of the art in automatic speech processing (notably recognition) is dominated by large pre-trained models that are meant to be used as black-boxes. In this work, we integrate a physiologically plausible (albeit simple filter-based) model of the cochlea into a much larger pre-trained acoustic model for speech recognition. We show that the hybrid system can be trained and evaluated with various combinations of fine-tuning and self-supervision. The results broadly show that the system automatically yields structures that are known to work well. Moreover, these structures lack artifacts that were apparent in (our) previous work using less sophisticated neural models. We conclude that the hybrid structure is an appropriate way to proceed in auditory research, more generally allowing the work to take advantage of larger models and databases from which it would not otherwise benefit.
More
Translated text
Key words
cochlear models,self-supervision,trainable filterbanks
AI Read Science
Must-Reading Tree
Example
Generate MRT to find the research sequence of this paper
Chat Paper
Summary is being generated by the instructions you defined