Results 141 to 150 of about 231,551 (186)

Multimodal Speaker Diarization

open access: yesIEEE Transactions on Pattern Analysis and Machine Intelligence, 2012
We present a novel probabilistic framework that fuses information coming from the audio and video modality to perform speaker diarization. The proposed framework is a Dynamic Bayesian Network (DBN) that is an extension of a factorial Hidden Markov Model (fHMM) and models the people appearing in an audiovisual recording as multimodal entities that ...
Athanasios K. Noulas   +2 more
openaire   +4 more sources

Speaker Recognition and Diarization

open access: yes, 2010
Item does not contain ...
Friedland, G., Leeuwen, D.A. van
openaire   +3 more sources

Pyannote.Audio: Neural Building Blocks for Speaker Diarization

open access: yes, 2020
We introduce pyannote.audio, an open-source toolkit written in Python for speaker diarization. Based on PyTorch machine learning framework, it provides a set of trainable end-to-end neural building blocks that can be combined and jointly optimized to ...
Pavel Korshunov   +2 more
exaly   +2 more sources

Speaker diarization in meeting audio

2009 IEEE International Conference on Acoustics, Speech and Signal Processing, 2009
This paper describes speaker diarization system on a NIST Rich Transcription 2007 (RT-07) Meeting Recognition evaluation data set for the task of Multiple Distant Microphone (MDM). Our implementation includes three components: initial clustering, non-speech removal and cluster purification.
Tin Lay Nwe   +3 more
openaire   +2 more sources

Speaker Diarization in Vietnamese Voice

2021
Speaker diarization is the process of partitioning an input audio stream into homogeneous segments according to different speakers. It is an important process to support speaker recognition systems and identify a speaker in broadcasts, meeting recordings, and voice mail.
Nguyen Duc Nam, Hieu Trung Huynh
openaire   +1 more source

DiCoW: Diarization-Conditioned Whisper for Target Speaker Automatic Speech Recognition [PDF]

open access: yesComputer Speech and Language
Speaker-attributed automatic speech recognition (ASR) in multi-speaker environments remains a significant challenge, particularly when systems conditioned on speaker embeddings fail to generalize to unseen speakers.
Jiangyu Han   +2 more
exaly   +1 more source

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