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- W3158354597 abstract "Automatic speech recognition (ASR) is one of the major research field in computer science. ASR is one of the most necessary tools, which is required for, almost every languages. But every language has its own techniques and highlights. In past years, significant number of mentionable research has already been done in this field. And the exactness of ASR mostly depends on the noise reduction process. This is the fundamental requirement of Speech data preprocessing . There are various way of data preprocessing for speech recognition. In this paper we discuss very effective way for preprocessing technique of Bangla speech data. We demonstrate the whole process of recording, then digitizing the data, removing noise with respect to signal (SNR), transforming the signal into Fourier transformation (FFT) for time domain to frequency domain, it would be better if result frames are chunked into small window, and finally apply Mel frequency cepstral coefficients (MFCC) algorithm to make data into respective vector representation so that, data is ready for training in neural network." @default.
- W3158354597 created "2021-05-10" @default.
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- W3158354597 date "2021-01-01" @default.
- W3158354597 modified "2023-09-27" @default.
- W3158354597 title "A Global Data Pre-processing Technique for Automatic Speech Recognition" @default.
- W3158354597 cites W2327501763 @default.
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- W3158354597 doi "https://doi.org/10.1007/978-981-33-4367-2_19" @default.
- W3158354597 hasPublicationYear "2021" @default.
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