Comparison of Vq and Dtw Classifiers for Speaker Verification

نویسنده

  • A M Ariyaeeinia
چکیده

An investigation into the relative speaker verification performance of various types of vector quantisation (VQ) and dynamic time warping (DTW) classifiers is presented. The study covers a number of algorithmic issues involved in the above classifiers, and examines the effects of these on the verification accuracy. The experiments are based on the use of a subset from the Brent (telephone quality) speech database. This subset consists of repetitions of isolated digit utterances 1 to 9 and zero. The paper describes the experimental work, and presents an analysis of the results.

برای دانلود رایگان متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Using Exciting and Spectral Envelope Information and Matrix Quantization for Improvement of the Speaker Verification Systems

Speaker verification from talking a few words of sentences has many applications. Many methods as DTW, HMM, VQ and MQ can be used for speaker verification. We applied MQ for its precise, reliable and robust performance with computational simplicity. We also used pitch frequency and log gain contour for further improvement of the system performance.

متن کامل

Using Exciting and Spectral Envelope Information and Matrix Quantization for Improvement of the Speaker Verification Systems

Speaker verification from talking a few words of sentences has many applications. Many methods as DTW, HMM, VQ and MQ can be used for speaker verification. We applied MQ for its precise, reliable and robust performance with computational simplicity. We also used pitch frequency and log gain contour for further improvement of the system performance.

متن کامل

Speaker recognition models

This paper evaluates continuous density hidden Markov models (CDHMM), dynamic time warping (DTW) and distortion-based vector quantisa-tion (VQ) for speaker recognition, across incremen-tal amounts of training data. In comparing VQ and CDHMMs for text-independent (TI) speaker recognition , it is shown that VQ performs better than an equivalent CDHMM with one training version, but is outperformed...

متن کامل

I Summary of Best Ti and Td Vq Performance Speaker Recognition Using Hidden Markov Models, Dynamic Time Warping and Vector Quantisation

1 Illustration of the segmentation of the database collected over a period of three months into training and 3 %Error against total number of mixtures for TI ergodic CDHMMs (10 version training) 7 %Error against the number of training versions for a TI 32 element VQ, and 32 mixture single state CDHMM 11 8 %Error against the number of training versions for TD DTW, 8 element VQ and 1 mixture 8 st...

متن کامل

Linear and non-linear fusion of ALISP-based and GMM systems for text-independent speaker verification

Current state-of-the-art speaker verification algorithms use Gaussian Mixture Models (GMM) to estimate the probability density function of the acoustic feature vectors. They are denoted here as global systems. In order to give better performance, they have to be combined with other classifiers, using different fusion methods. The performance of the final classifier depend on the choice of the s...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 2004