An acoustic echo canceller optimized for hands-free speech telecommunication in large vehicle cabins

EURASIP Journal on Audio, Speech, and Music Processing

Empirical Research

Zonghua Gu¹  Ghazaleh Ghaffari¹  Amin Saremi²  Balaji Ramkumar³ 

[1] Department of Applied Physics and Electronics, Umeå University, 901 87, Umeå, Sweden;Department of Applied Physics and Electronics, Umeå University, 901 87, Umeå, Sweden;Department of Electronics, and Connected Services (EACS), Volvo Technology, 417 15, Göteborg, Sweden;Department of Statistics and Machine Learning, Linköping University, 581 83, Linköping, Sweden;

关键词: Speech signal enhancement;    Automotive speech processing;    Acoustic echo cancelation;    Adaptive filters;    NLMS;    Keyword spotting;    Hands-free telephony;    Automotive voice assistant;   

DOI  :  10.1186/s13636-023-00305-7

 received in 2023-02-27, accepted in 2023-09-09,  发布年份 2023

来源: Springer

【 摘 要 】

Acoustic echo cancelation (AEC) is a system identification problem that has been addressed by various techniques and most commonly by normalized least mean square (NLMS) adaptive algorithms. However, performing a successful AEC in large commercial vehicles has proved complicated due to the size and challenging variations in the acoustic characteristics of their cabins. Here, we present a wideband fully linear time domain NLMS algorithm for AEC that is enhanced by a statistical double-talk detector (DTD) and a voice activity detector (VAD). The proposed solution was tested in four main Volvo truck models, with various cabin geometries, using standard Swedish hearing-in-noise (HINT) sentences in the presence and absence of engine noise. The results show that the proposed solution achieves a high echo return loss enhancement (ERLE) of at least 25 dB with a fast convergence time, fulfilling ITU G.168 requirements. The presented solution was particularly developed to provide a practical compromise between accuracy and computational cost to allow its real-time implementation on commercial digital signal processors (DSPs). A real-time implementation of the solution was coded in C on an ARM Cortex M-7 DSP. The algorithmic latency was measured at less than 26 ms for processing each 50-ms buffer indicating the computational feasibility of the proposed solution for real-time implementation on common DSPs and embedded systems with limited computational and memory resources. MATLAB source codes and related audio files are made available online for reference and further development.

【 授权许可】

CC BY   
© Springer Nature Switzerland AG 2023

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