Probabilistic Self-Organizing Maps for Text-Independent Speaker Identification
نویسندگان
چکیده
منابع مشابه
Text independent speaker identification on noisy environments by means of self organizing maps
In this paper we propose a new architecture for speaker recognition. This architecture is independent of the text, robust with the presence of noise, and is based on the Self Organizing Maps (SOM) [I]. We compare the performance of this architectue for different parameuizations, different signal to noise ratios, with another method for speaker identification based on the arithmetic-harmonic sph...
متن کاملText-Independent Speaker Identification
Speaker identification is a difficult task, and the task has several different approaches. The state of the art for speaker identification techniques include dynamic time warped(DTW) template matching, Hidden Markov Modeling(HMM), and codebook schemes based on vector quantization(VQ)[2]. In this project, the vector quantization approach will be used, due to ease of implementation and high accur...
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We present a self-organizing map model to study qualitative data (also called categorical data). It is based on a probabilistic framework which does not assume any prespecified distribution of the input data. Stochastic approximation theory is used to develop a learning rule that builds an approximation of a discrete distribution on each unit. This way, the internal structure of the input datas...
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Neural Networks are analytic techniques modeled after the (hypothesized) processes of learning in the cognitive system and the neurological functions of the brain and capable of predicting new observations (on specific variables) from other observations (on the same or other variables) after executing a process of so-called learning from existing data. Artificial Neural Networks are relatively ...
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A new approach is presented for clustering the speakers from unlabeled and unsegmented conversation, when the number of speakers is unknown. In this approach, each speaker is modeled by a SelfOrganizing-Map (SOM). For estimation of the number of clusters the Bayesian Information Criterion (BIC) is applied. This approach was tested on the NIST 1996 HUB-4 evaluation test in terms of speaker and c...
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ژورنال
عنوان ژورنال: TELKOMNIKA (Telecommunication Computing Electronics and Control)
سال: 2018
ISSN: 2302-9293,1693-6930
DOI: 10.12928/telkomnika.v16i1.7559