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T-test distance and clustering criterion for speaker diarization (2008)
| Content Provider | CiteSeerX |
|---|---|
| Author | Nguyen, Trung Hieu Chng, Eng Siong Li, Haizhou |
| Description | In this paper, we present an application of student’s t-test to measure the similarity between two speaker models. The mea-sure is evaluated by comparing with other distance metrics: the Generalized Likelihood Ratio, the Cross Likelihood Ratio and the Normalized Cross Likelihood Ratio in speaker detec-tion task. We also propose an objective criterion for speaker clustering. The criterion deduces the number of speakers auto-matically by maximizing the separation between intra-speaker distances and inter-speaker distances. It requires no develop-ment data and works well with various distance metrics. We then report the performance of our proposed similarity distance measure and objective criterion in speaker diarization task. The system produces competitive results: low speaker diarization error rate and high accuracy in detecting number of speakers. Index Terms: speaker diarization, speaker detection, intra-speaker, inter-speaker. In Interspeech 2008 |
| File Format | |
| Language | English |
| Publisher Date | 2008-01-01 |
| Access Restriction | Open |
| Subject Keyword | Speaker Diarization Task Competitive Result Generalized Likelihood Ratio Speaker Model Low Speaker Diarization Error Rate Speaker Detection Speaker Diarization Student T-test Various Distance Metric High Accuracy Speaker Clustering Intra-speaker Distance Speaker Detec-tion Task Normalized Cross Likelihood Ratio T-test Distance Distance Metric Develop-ment Data Index Term Similarity Distance Measure Inter-speaker Distance Cross Likelihood Ratio Objective Criterion |
| Content Type | Text |
| Resource Type | Article |
