A Review on Speech Recognition Technique

Gaikwad, Santosh; Gawali, Bharti; Yannawar, Pravin

doi:10.5120/1462-1976

Cited by 228 publications

(104 citation statements)

References 20 publications

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“…Speech is, however, a dynamic process without clearly distinguished parts. It converts the spoken words into text form exactly in the similar way that the user pronounces [8].All modern descriptions of speech are to some degree probabilistic. That means that there are no certain boundaries between units, or between words.…”

Section: Speech-to-text (Stt)mentioning

confidence: 99%

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A Sophisticated HCI Perspective: Advanced Bengali Phonetics Communication System for Disabled (Deaf and Dumb) Persons

Sakib¹,

Amlan²,

Islam³

et al. 2017

IJCA

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The purpose of this study is to develop an intelligent system that can help the people who are dumb and deaf as they are recognized as disabled persons. These people face difficulties in communicating with other people in their regular life activities such as travelling, shopping etc. Nowadays, Human Computer Interaction (HCI) domain facing and solving the problem of disabled persons of this day to day activities. In this paper a new solution of this problem and the perspective of HCI is being focused. This paper is synthesized and analyzed speech-to-text (STT) and text-to-speech (TTS) algorithms to implement the system for those people who are deaf & dumb. The system will behave and act on behalf of the person and it will also capture the words from the other side and convert it to text, thus the deaf person may understand others say through the display of this system. There is a huge amount of people who are deaf and dumb in Bangladesh. Therefore, the system has been implemented both in Bengali phonetics & English language. The performance of this paper showed a satisfactory result of this system.

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Section: Speech-to-text (Stt)mentioning

confidence: 99%

“…Speech to text translation and other applications of speech are never been 100% correct. It works like a continuous audio stream where stable states may mix with dynamically unstable states [8].…”

Section: Speech-to-text (Stt)mentioning

confidence: 99%

A Sophisticated HCI Perspective: Advanced Bengali Phonetics Communication System for Disabled (Deaf and Dumb) Persons

Sakib¹,

Amlan²,

Islam³

et al. 2017

IJCA

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show abstract

“…The artificial intelligence approach is a combination of both the acoustic-phonetic approach and the pattern recognition approach. This method is used to automatically recognize speech by applying the same type of intelligence that human uses to make decisions based on a set of measured acoustic features (Rabiner and Juang, 1993;Gaikwad et al, 2010). In this method, knowledge from a variety of sources such as acoustic knowledge, syntactic knowledge etc.…”

Section: Automatic Speech Recognitionmentioning

confidence: 99%

Automatic Recognition of Speech-evoked Brainstem Responses to English Vowels

Samimi

Forouzanfar

Dajani

2015

Modelling, Identification and Control / 827: Computational Intelligence

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The objective of this study is to investigate automatic recognition of speech-evoked auditory brainstem responses (speech-evoked ABR) to the five English vowels (/a/, /ae/, /ao (ɔ)/, /i/ and /u/). We used different automatic speech recognition methods to discriminate between the responses to the vowels. The best recognition result was obtained by applying principal component analysis (PCA) on the amplitudes of the first ten harmonic components of the envelope following response (based on spectral components at fundamental frequency and its harmonics) and of the frequency following response (based on spectral components in first formant region) and combining these two feature sets. With this combined feature set used as input to an artificial neural network, a recognition accuracy of 83.8% was achieved. This study could be extended to more complex stimuli to improve assessment of the auditory system for speech communication in hearing impaired individuals, and potentially help in the objective fitting of hearing aids.iii

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“…After warping the numbers of coefficients are obtained. Finally the Inverse Discrete Fourier Transformer is used for the Cepstral coefficients calculation [8] [9]. It transforms the log of the quefrench domain coefficients to the frequency domain where N is the length of the DFT.…”

Section: B Mel Frequency Cepstral Coefficients (Mfcc)mentioning

confidence: 99%