In this paper, we propose a method to extract and verify individual speaker utterance using a subspace method. This method can extract speech section of the same speaker by repeating speaker verification between the present speech section and the immediately previous speech section. The speaker models are automatically trained in the verification process without constructing speaker templates i...

This paper addresses the problem of speaker verification in two speaker conversations, proposing a set of confidence measures to assess the quality of a given speaker segmentation. We study how these measures can be used to estimate the performance of a state-of-the-art speaker verification system, the I3A submission for the core-summed condition in the NIST SRE 2010. We present a Factor Analys...

In this paper, we propose a method to extract and verify individual speaker utterance using a subspace method. This method can extract speech section of the same speaker by repeating speaker verification between the present speech section and the immediately previous speech section. The speaker models are automatically trained in the verification process without constructing speaker templates i...

This paper addresses the problem of speaker verification in two speaker conversations, proposing a set of confidence measures to assess the quality of a given speaker segmentation. We study how these measures can be used to estimate the performance of a state-of-the-art speaker verification system, the I3A submission for the core-summed condition in the NIST SRE 2010. We present a Factor Analys...

This paper describes methods to determine thresholds for speaker verification. Setting an appropriate threshold a priori is difficult because likelihood verification covers a wide range and the appropriate threshold for each speaker is different. We propose new methods to determine the speaker verification threshold depending on the "adaptation degree" for each speaker. We use the gain in likel...

Speaker verification based on phone modelling is examined in this paper. Phone modelling is attractive, because different phonemes have different levels of usefulness for speaker recognition, and because phone modelling essentially makes a speaker verification algorithm text independent. The speaker verification system used here is based on a two stage approach, where speech recognition (segmen...

In speaker recognition, it is a problem that variation of speech features is caused by sentences and time difference. Speech data includes a phonetic information and a speaker information. If they are separated each other, robust speaker verification will be realized by using only the speaker information. However, it is difficult to separate the speaker information from the phonetic information...

This paper addresses the problem of speaker verification in two speaker conversations, proposing a set of confidence measures to assess the quality of a given speaker segmentation. In addition we study how these measures can be used to estimate the performance of a state of the art speaker verification system. Our approach for speaker segmentation is based on the eigenvoice paradigm. We present...

In anchor modeling, each speaker utterance is represented as a fixed-length location vector in the space of reference speakers by scoring against a set of anchor models. SVMbased speaker verification systems using the anchor location representation have been studied in previously reported work with promising results. In this paper, linear combination weights in reference speaker weighting (RSW)...

In this paper, we propose a novel speaker verification method which determines whether a claimer is accepted or rejected by the rank of the claimer in a large number of speaker models instead of score normalization, such as T-norm and Z-norm. The method has advantages over the standard T-norm in speaker verification accuracy. However, it needs much computation time as well as T-norm that needs ...