Underwater Diver Communication System Based on Speech/Text Conversion

Underwater acoustic (UA) communication system has low data rate due to the limited bandwidth of the UA channel. This makes real-time speech communication challenging. In this paper, we present an underwater diver communication system which uses speech-to-text conversion at the transmitter to achieve speech compression. The text message is converted back to speech at the receiver end using text-to-speech conversion. Automatic speech recognition (ASR) models including Wav2vec2 and Whisper are investigated for their feasibility of real-time conversion. A prototype underwater diver speech communication system utilizing Raspberry Pi 5 is presented in the paper. The system design encompasses both the transmitting and receiving processes, with a focus on its real-time capabilities. We discuss the performance of this diver communication system, validating its efficacy through an experiment conducted in Fremantle, Western Australia. It is shown that with the Whisper-base model, real-time communication is achieved with an average word error rate of 2.4%.

Authors

Institutions

Publication Details

Published
2025-06-16
DOI
https://doi.org/10.1109/oceans58557.2025.11104740
Primary Topic
Underwater Vehicles and Communication Systems
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Underwater Diver Communication System Based on Speech/Text Conversion

Peng Chen, Nan Zheng, Yue Rong
Underwater Vehicles and Communication Systems
article

Underwater Diver Communication System Based on Speech/Text Conversion

Peng Chen, Nan Zheng, Yue Rong
article en

Abstract

Underwater acoustic (UA) communication system has low data rate due to the limited bandwidth of the UA channel. This makes real-time speech communication challenging. In this paper, we present an underwater diver communication system which uses speech-to-text conversion at the transmitter to achieve speech compression. The text message is converted back to speech at the receiver end using text-to-speech conversion. Automatic speech recognition (ASR) models including Wav2vec2 and Whisper are investigated for their feasibility of real-time conversion. A prototype underwater diver speech communication system utilizing Raspberry Pi 5 is presented in the paper. The system design encompasses both the transmitting and receiving processes, with a focus on its real-time capabilities. We discuss the performance of this diver communication system, validating its efficacy through an experiment conducted in Fremantle, Western Australia. It is shown that with the Whisper-base model, real-time communication is achieved with an average word error rate of 2.4%.

Curtin University (AU), UNSW Sydney (AU)
Quality Education
Openalex Percentile: Top 75%
Underwater Vehicles and Communication Systems
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.