Purpose: A major barrier to the wider use of language sample analysis (LSA) is the fact that
transcription is very time intensive. Methods that can reduce the required time and effort …

Deep neural network-based systems have significantly improved the performance of
speaker diarization tasks. However, end-to-end neural diarization (EEND) systems often …

We propose a modular pipeline for the single-channel separation, recognition, and
diarization of meeting-style recordings and evaluate it on the Libri-CSS dataset. Using a …

Multi-talker overlapped speech poses a significant challenge for speech recognition and
diarization. Recent research indicated that these two tasks are inter-dependent and …

Speaker diarization is the partitioning of an audio source stream into homogeneous
segments according to the speaker's identity. It can improve the readability of an automatic …

Speaker recognition is often dependent on the speaker and susceptible to emotional factors,
thus mostly decreasing recognition performance, we propose a framework by combining …