A comparative study of performance of fpga based mel filter bank & bark filter bank

نویسندگان

  • Debalina Ghosh
  • Depanwita Sarkar Debnath
  • Saikat Bose
چکیده

The sensitivity of human ear is dependent on frequency which is nonlinearly resolved across the audio spectrum .Now to improve the recognition performance in a similar non linear approach requires a front end design, suggested by empirical evidences. A popular alternative to linear prediction based analysis is therefore filter bank analysis since this provides a much more straightforward route to obtain the desired non-linear frequency resolution. MEL filter bank and BARK filter bank are two popular filter bank analysis techniques. This paper presents FPGA based implementation of MEL filter bank and BARK filter bank with different bandwidths and different signal spectrum ranges. The designs have been implemented using VHDL, simulated and verified using Xilinx 11.1.For each filter bank, the basic building block is implemented in Spartan 3E. A comparative study among these two mentioned filter banks is also done in this paper. .

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

Auditory Scale Analysis and Evaluation of Phonemes in MISING Language

Frequency analyzer is one of the important functions of peripheral auditory system. Psycho-acoustically this gives rise to the concept of critical band, which represents the frequency resolution of the auditory system. Mel-Scale warping is one of the common techniques used for the analysis in speech recognition. Bark and ERB (Equivalent Rectangular Bandwidth) rate scales are two other auditory ...

متن کامل

Filter Bank Feature Extraction for Gaussian Mixture Model Speaker Recognition

Speaker Recognition is the task of identifying an individual from their voice. Typically this task is performed in two consecutive stages: feature extraction and classification. Using a Gaussian Mixture Model (GMM) classifier different filter-bank configurations were compared as feature extraction techniques for speaker recognition. The filter-banks were also compared to the popular Mel-Frequen...

متن کامل

A Bark-scale filter bank approach to independent component analysis for acoustic mixtures

Uniform filter bank approach can be considered to perform independent component analysis (ICA) for convolved mixtures. It achieves better separation performance than the frequency domain approach and gives faster convergence speed with less computational complexity than the time domain approach. However, when the uniform filter bank approach is applied to natural audio signals, for high frequen...

متن کامل

A Framework for Multilingual Text- Independent speaker identification System

This article evaluates the performance of Extreme Learning Machine (ELM) and Gaussian Mixture Model (GMM) in the context of text independent Multi lingual speaker identification for recorded and synthesized speeches. The type and number of filters in the filter bank, number of samples in each frame of the speech signal and fusion of model scores play a vital role in speaker identification accur...

متن کامل

Improving the performance of MFCC for Persian robust speech recognition

The Mel Frequency cepstral coefficients are the most widely used feature in speech recognition but they are very sensitive to noise. In this paper to achieve a satisfactorily performance in Automatic Speech Recognition (ASR) applications we introduce a noise robust new set of MFCC vector estimated through following steps. First, spectral mean normalization is a pre-processing which applies to t...

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:
  • CoRR

دوره abs/1206.1450  شماره 

صفحات  -

تاریخ انتشار 2012