A Noise-Robust Continuous Speech Recognition System Using Block-Based Dynamic Range Adjustment

نویسندگان

  • Yiming Sun
  • Yoshikazu Miyanaga
چکیده

SUMMARY A new approach to speech feature estimation under noise circumstances is proposed in this paper. It is used in noise-robust continuous speech recognition (CSR). As the noise robust techniques in isolated word speech recognition, the running spectrum analysis (RSA), the running spectrum filtering (RSF) and the dynamic range adjustment (DRA) methods have been developed. Among them, only RSA has been applied to a CSR system. This paper proposes an extended DRA for a noise-robnst CSR system. In the stage of speech recognition, a continuous speech waveform is automatically assigned to a block defined by a short time length. The extended DRA is applied to these estimated blocks. The average recognition rate of the proposed method has been improved under several different noise conditions. As a result, the recognition rates are improved up to 15% in various noises with 10 dB SNR.

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

An Efficient Block-based Dynamic Range Adjustment Method in Noise-robust Continuous Speech Recognition

This paper proposes a new technique for speech feature estimation under noise circumstances. This new approach yields noise-robust continuous speech recognition (CSR). Noiserobust techniques for isolated word speech recognition typically employ the running spectrum analysis (RSA), the running spectrum filtering (RSF) and the dynamic range adjustment (DRA) methods. Among them, only RSA has been ...

متن کامل

Robust Speech Recognition with MSC/DRA Feature Extraction on Modulation Spectrum Domain

This report introduces noise robust speech recognition and proposes advanced speech analysis techniques named MSC (Modulation Spectrum Control)/DRA (Dynamic Range Adjustment). The dynamic range of cepstrum obtained from noisy speech is usually smaller than that from the same speech without noise since some speech features are hidden in noise. This difference may cause recognition errors. Theref...

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

A Real Time Noise-Robust Speech Recognition System

This paper introduces the extraction of speech features realizing noise robustness for speech recognition. It also explores advanced speech analysis techniques named RSF (Running Spectrum Filtering)/DRA (Dynamic Range Adjustment) in detail. The new experiments on phase recognition were carried out using 40 male and female speakers for training and 5 other male and female speakers for recognitio...

متن کامل

روشی جدید در بازشناسی مقاوم گفتار مبتنی بر دادگان مفقود با استفاده از شبکه عصبی دوسویه

Performance of speech recognition systems is greatly reduced when speech corrupted by noise. One common method for robust speech recognition systems is missing feature methods. In this way, the components in time - frequency representation of signal (Spectrogram) that present low signal to noise ratio (SNR), are tagged as missing and deleted then replaced by remained components and statistical ...

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:
  • IEICE Transactions

دوره 95-D  شماره 

صفحات  -

تاریخ انتشار 2012