Early recognition of speech

نویسندگان

  • Robert E Remez
  • Emily F Thomas
چکیده

Classic research on the perception of speech sought to identify minimal acoustic correlates of each consonant and vowel. In explaining perception, this view designated momentary components of an acoustic spectrum as cues to the recognition of elementary phonemes. This conceptualization of speech perception is untenable given the findings of phonetic sensitivity to modulation independent of the acoustic and auditory form of the carrier. The empirical key is provided by studies of the perceptual organization of speech, a low-level integrative function that finds and follows the sensory effects of speech amid concurrent events. These projects have shown that the perceptual organization of speech is keyed to modulation; fast; unlearned; nonsymbolic; indifferent to short-term auditory properties; and organization requires attention. The ineluctably multisensory nature of speech perception also imposes conditions that distinguish language among cognitive systems. WIREs Cogn Sci 2013, 4:213-223. doi: 10.1002/wcs.1213 This article is categorized under: Psychology > Language.

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

Speech Emotion Recognition Based on Power Normalized Cepstral Coefficients in Noisy Conditions

Automatic recognition of speech emotional states in noisy conditions has become an important research topic in the emotional speech recognition area, in recent years. This paper considers the recognition of emotional states via speech in real environments. For this task, we employ the power normalized cepstral coefficients (PNCC) in a speech emotion recognition system. We investigate its perfor...

متن کامل

A Database for Automatic Persian Speech Emotion Recognition: Collection, Processing and Evaluation

Abstract   Recent developments in robotics automation have motivated researchers to improve the efficiency of interactive systems by making a natural man-machine interaction. Since speech is the most popular method of communication, recognizing human emotions from speech signal becomes a challenging research topic known as Speech Emotion Recognition (SER). In this study, we propose a Persian em...

متن کامل

Early Posterior Negativity as Facial Emotion Recognition Index in Children With Attention Deficit Hyperactivity Disorder

Introduction: Studies indicate that children with Attention Deficit Hyperactivity Disorder (ADHD) have deficits in social and emotional functions. It can be hypothesized that these children have some deficits in early stages of facial emotion discrimination. Based on this hypothesis, the present study investigated neural correlates of early visual processing during emotional face recognition in...

متن کامل

Statistical Variation Analysis of Formant and Pitch Frequencies in Anger and Happiness Emotional Sentences in Farsi Language

Setup of an emotion recognition or emotional speech recognition system is directly related to how emotion changes the speech features. In this research, the influence of emotion on the anger and happiness was evaluated and the results were compared with the neutral speech. So the pitch frequency and the first three formant frequencies were used. The experimental results showed that there are lo...

متن کامل

Persian Phone Recognition Using Acoustic Landmarks and Neural Network-based variability compensation methods

Speech recognition is a subfield of artificial intelligence that develops technologies to convert speech utterance into transcription. So far, various methods such as hidden Markov models and artificial neural networks have been used to develop speech recognition systems. In most of these systems, the speech signal frames are processed uniformly, while the information is not evenly distributed ...

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:

دوره 4  شماره 

صفحات  -

تاریخ انتشار 2013