Similarity-and-independence-aware Beamformer With Iterative Casting And Boost Start For Target Source Extraction Using Reference

Abstract

Target source extraction is significant for improving human speech intelligibility and the speech recognition performance of computers. This study describes a method for target source extraction, called the similarity-and-independence-aware beamformer (SIBF). The SIBF extracts the target source using a rough magnitude spectrogram as the reference signal. The advantage of the SIBF is that it can obtain a more accurate signal than the spectrogram generated by target-enhancing methods such as speech enhancement based on deep neural networks. For the extraction, we extend the framework of deflationary independent component analysis (ICA) by considering the similarities between the reference and extracted target sources, in addition to the mutual independence of all the potential sources. To solve the extraction problem by maximum-likelihood estimation, we introduce three source models that can reflect the similarities. The major contributions of this study are as follows. First, the extrac

Stats

• citations5
• S2 citations—
• github stars0
• HF likes0
• heat score5.84
• arxiv keyhiroe2021similarity

Related papers

• Similarity-and-independence-aware Beamformer: Method For Target Source Extraction Using Magnitude Spectrogram As Reference (2020)2.26
• Improving Speaker Discrimination Of Target Speech Extraction With Time-domain Speakerbeam (2020)14.76
• Optimization Of Speaker Extraction Neural Network With Magnitude And Temporal Spectrum Approximation Loss (2019)11.29
• Statistical Beamformer Exploiting Non-stationarity And Sparsity With Spatially Constrained ICA For Robust Speech Recognition (2023)0.00
• Dual-path Transformer Based Neural Beamformer For Target Speech Extraction (2023)0.00
• Enhanced Neural Beamformer With Spatial Information For Target Speech Extraction (2023)2.26
• Neural Network-based Time-frequency-bin-wise Linear Combination Of Beamformers For Underdetermined Target Source Extraction (2026)0.00
• Target Speech Extraction: Independent Vector Extraction Guided By Supervised Speaker Identification (2021)8.09