7 accepted papers
In contrast to human speech, machine-generated sounds of the same type often exhibit consistent frequency characteristics and discernible temporal periodicity. However, leveraging these dual attributes in anomaly detection remains relatively under-explored. In this paper, we propose an automated dua…
Personal voice activity detection (PVAD) is gradually used in speech assistants. Traditional PVAD schemes extract the target speaker’s embedding from existing query reference speech through a pre-trained speaker verification model. Consequently, the performance of the PVAD model may suffer if the qu…
The deep neural networks, such as the Deep-FSMN, have been widely studied for keyword spotting (KWS) applications. However, computational resources for these networks are significantly constrained since they usually run on-call on edge devices. In this paper, we present BiFSMN, an accurate and extre…
This paper describes our submission to ICASSP 2022 Multi-channel Multi-party Meeting Transcription (M2MeT) Challenge. For Track 1, we propose several approaches to make the clustering-based speaker diarization system enable to handle overlapped speech. Front-end dereverberation and the direction-of-…
The recurrent neural network transducer (RNN-T) model has been proved effective for keyword spotting (KWS) recently. However, compared with cross-entropy (CE) or connectionist temporal classification (CTC) based models, the additional prediction network in the RNN-T model increases the model size an…
With the advent of recurrent neural network transducer (RNN-T) model, the performance of keyword spotting (KWS) systems has greatly improved. However, the KWS systems, employed for wake-word detection, still rely on the availability of keyword specific training data for achieving reasonable performa…
Recently, a hybrid deep neural network/i-vector framework has been proved effective for speaker verification, where the DNN trained to predict tied-triphone states (senones) is used to produce frame alignments for sufficient statistics extraction. In this work, in order to better understand the impa…