The use of harmonic features in speaker recognition

نویسندگان

  • Bojan Imperl
  • Zdravko Kacic
  • Bogomir Horvat
چکیده

In this paper the Harmonic features based on the harmonic decomposition of the Hildebrand { Prony line spectrum are introduced. A Hildebrand { Prony method of spectral analysis was applied because of its high resolution and accuracy. Comparative tests with the LP and LP { cepstral features were made with 50 speakers from the Slovene database SNABI (isolated words corpus) and 50 speakers of the German database BAS Siemens 100 (utterances of sentences). With both databases the advantages of the Harmonic features were noticed especially for the speaker identi cation while for the speaker veri cation the Harmonic features have performed better on the SNABI database and as good as the LP cepstral features on the BAS Siemens 100 database.

برای دانلود 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

شبکه عصبی پیچشی با پنجره‌های قابل تطبیق برای بازشناسی گفتار

Although, speech recognition systems are widely used and their accuracies are continuously increased, there is a considerable performance gap between their accuracies and human recognition ability. This is partially due to high speaker variations in speech signal. Deep neural networks are among the best tools for acoustic modeling. Recently, using hybrid deep neural network and hidden Markov mo...

متن کامل

Speaker Adaptation in Continuous Speech Recognition Using MLLR-Based MAP Estimation

A variety of methods are used for speaker adaptation in speech recognition. In some techniques, such as MAP estimation, only the models with available training data are updated. Hence, large amounts of training data are required in order to have significant recognition improvements. In some others, such as MLLR, where several general transformations are applied to model clusters, the results ar...

متن کامل

Speaker Adaptation in Continuous Speech Recognition Using MLLR-Based MAP Estimation

A variety of methods are used for speaker adaptation in speech recognition. In some techniques, such as MAP estimation, only the models with available training data are updated. Hence, large amounts of training data are required in order to have significant recognition improvements. In some others, such as MLLR, where several general transformations are applied to model clusters, the results ar...

متن کامل

Classification of emotional speech using spectral pattern features

Speech Emotion Recognition (SER) is a new and challenging research area with a wide range of applications in man-machine interactions. The aim of a SER system is to recognize human emotion by analyzing the acoustics of speech sound. In this study, we propose Spectral Pattern features (SPs) and Harmonic Energy features (HEs) for emotion recognition. These features extracted from the spectrogram ...

متن کامل

Use of the Harmonic Phase in Speaker Recognition

In this paper a novel set of features with a promising ability to identify speakers is presented. These features are based on the harmonic phase of the speech signal and have been previously used successfully in an ASR task. Using the SI-284 subset of the WSJ database, a GMM has been trained for each of the 283 speakers and several speaker identification experiments have been performed, with a ...

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

برای دانلود 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

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 1997