Papers
arxiv:2312.05815

Voice Activity Detection (VAD) in Noisy Environments

Published on Dec 10, 2023
Authors:

Abstract

A novel Voice Activity Detection system is developed with enhanced filtering techniques to accurately distinguish speech from noise in challenging acoustic environments.

AI-generated summary

In the realm of digital audio processing, Voice Activity Detection (VAD) plays a pivotal role in distinguishing speech from non-speech elements, a task that becomes increasingly complex in noisy environments. This paper details the development and implementation of a VAD system, specifically engineered to maintain high accuracy in the presence of various ambient noises. We introduce a novel algorithm enhanced with a specially designed filtering technique, effectively isolating speech even amidst diverse background sounds. Our comprehensive testing and validation demonstrate the system's robustness, highlighting its capability to discern speech from noise with remarkable precision. The exploration delves into: (1) the core principles underpinning VAD and its crucial role in modern audio processing; (2) the methodologies we employed to filter ambient noise; and (3) a presentation of evidence affirming our system's superior performance in noisy conditions.

Community

Sign up or log in to comment

Get this paper in your agent:

hf papers read 2312.05815
Don't have the latest CLI?
curl -LsSf https://hf.co/cli/install.sh | bash

Models citing this paper 0

No model linking this paper

Cite arxiv.org/abs/2312.05815 in a model README.md to link it from this page.

Datasets citing this paper 0

No dataset linking this paper

Cite arxiv.org/abs/2312.05815 in a dataset README.md to link it from this page.

Spaces citing this paper 0

No Space linking this paper

Cite arxiv.org/abs/2312.05815 in a Space README.md to link it from this page.

Collections including this paper 0

No Collection including this paper

Add this paper to a collection to link it from this page.