Phonetic subspace mixture model for speaker diarization
نویسندگان
چکیده
This paper presents an improved distance measure for speaker clustering in speaker diarization systems. The proposed phonetic subspace mixture (PSM) model introduces phonetic information to the BIC distance measure. Therefore, the new PSM model-based BIC distance measure can remove the effect of phonetic content on the diarization results. The typical BIC distance measure can be seen as a special case of the new BIC distance measure. Our experiment results show that the new distance measurement consistently improves the speaker diarization performance on three datasets.
منابع مشابه
The Approach of Speaker Diarization by Gaussian Mixture Model (GMM)
Speaker identification is an important activity in the process of speaker diarization. We need to model the speaker by Gaussian mixture model (GMM) for speaker identification purpose. Large GMM is called as a Universal Background Model (UBM) which is adapted into each speaker model for speaker identification purpose. This paper focuses on speech clustering for speaker diarization. The speaker d...
متن کاملSpeaker Diarization Using Gaussian Mixture Turns and Segment Matching
Speaker diarization aims to detect “who spoke when” in large audio segments. It is an important task in processing of broadcast news audio, making easier the audio segments selection and indexing task. In this paper an unsupervised speaker diarization scheme is proposed using a Gaussian Mixture Model as a Universal Background Model, Bayesian Information Criterion and fingerprint detection. A de...
متن کاملProsodic and Phonetic Features for Speaker Clustering in Speaker Diarization Systems
This work is focused on speaker clustering methods that are used in speaker diarization systems. The purpose of speaker clustering is to associate together segments that belong to the same speaker and is usually applied in the last stage of the speaker-diarization process. We concentrate on developing proper representations of speaker segments for clustering. We realize two different speaker cl...
متن کاملOn the use of GSV-SVM for Speaker Diarization and Tracking
In this paper, we present the use of Gaussian Supervectors with Support Vector Machines classifiers (GSV-SVM) in an acoustic speaker diarization and a speaker tracking system, compared with a standard Gaussian Mixture Model system based on adapted Universal Background Models (GMM-UBM). GSVSVM systems (which share the adaptation step with the GMMUBM systems) are observed to have comparable perfo...
متن کاملImproving Speaker Diarization
This paper describes the LIMSI speaker diarization system used in the RT-04F evaluation. The RT-04F system builds upon the LIMSI baseline data partitioner, which is used in the broadcast news transcription system. This partitioner provides a high cluster purity but has a tendency to split the data from a speaker into several clusters when there is a large quantity of data for the speaker. In th...
متن کامل